C-Means Clustering
Section: Fuzzy Clustering, Fuzzy Classification Techniques, Fuzzy C-Means (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
CAD
Definition:* Computer Assisted Design. Computer Assisted Diagnosis. A variety of meanings, depending on context.
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Graphics and CAD Based Vision, CAD Models (H1)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* CAD-Based 3D Object Representation for Robot Vision
* CAGD Based Computer Vision
* Organizing Large Structural Modelbases
* Precompiling a Geometric Model into an Interpretation Tree for Object Recognition in Bin-Picking Tasks
8 for CAD
CAD, Survey
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* CAD-Based Robot Vision
Cadastral Data
Section: GIS: Cadastral Data Storage and Use (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Calcification
Section: Mammography, Microcalcifications, Detection, Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Calibration Object
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration Using Calibration Object, or Known Features (H2)
Calibration
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Calibration -- Laser Scanner Multi-Path, Multipath (H4)
Section: Calibration -- LiDAR, Laser Scanner, Depth Sensor, Scanner Error Analysis (H3)
Section: Camera Calibration FengYun-3, FY-3, FY-4 (H2)
Section: Camera Calibration Techniques (H1)
Section: Camera Calibration ZY-3, ZiYuan-3 (H2)
Section: Camera Calibration, Perspective N Point Problem (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Laser Scanner Calibration -- Calgary Group, Lichti (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Radar Calibraion (H3)
Section: RGB-D Laser Scanner Calibration, Color and LIDAR (H4)
* Multi-View AAM Fitting and Camera Calibration
14 for Calibration
Calibration, Range Finder
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Projective Calibration of a Laser-Stripe Range Finder
Calibration, Self
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Self Calibration, Autocalibration, Auto-Calibration (H2)
Section: Camera Calibration, Stereo, Robot Based, Movable (H3)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Critical Motions and Ambiguous Euclidean Reconstructions in Auto-Calibration
* Multiview Geometry: Profiles and Self-Calibration
7 for Calibration, Self
Calibration, Stereo
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Self-Calibration of an Uncalibrated Stereo Rig from One Unknown Motion
Camera Calibration
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Atmospheric Corrections for Remote Sensing, Satellite and Space Images (H3)
Section: Calibration Using Line Features, Lines (H3)
Section: Camera Calibration FengYun-3, FY-3, FY-4 (H2)
Section: Camera Calibration Techniques (H1)
Section: Camera Calibration Using Calibration Object, or Known Features (H2)
Section: Camera Calibration ZY-3, ZiYuan-3 (H2)
Section: Camera Calibration, Lens Distortion, Aberration, Radial Distortion, Internal Parameters (H2)
Section: Camera Calibration, Perspective Based, Vanishing Points (H2)
Section: Camera Calibration, Perspective N Point Problem (H3)
Section: Camera Calibration, Photogrammetric, Bundle Adjustment, Block Adjustment (H2)
Section: Camera Calibration, Robot Based, Servo (H2)
Section: Camera Calibration, Self Calibration, Autocalibration, Auto-Calibration (H2)
Section: Camera Calibration, Stereo, Robot Based, Movable (H3)
Section: Camera Calibration, Stereo (H2)
Section: Camera Orientation Computations, Camera Calibration, Interior Orientation, Exterior Orientation (H2)
Section: Camera Pose (H2)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Catadioptric, Omnidirectional Camera Calibration, Fisheye Lens (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Photometric Calibration, Radiometric Calibration, Spectral Calibration, Color Calibration (H2)
Section: Pushbroom Camera Calibration Issues (H3)
Section: Radiometric Calibration of Remote Sensing, Satellite and Space Images (H3)
Section: Refractive, Water, Underwater Camera Calibration (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Section: Vignetting Correction, Vignetting Analysis (H3)
Section: Weakly Calibrated Cameras (H1)
Section: Zoom Lens Calibration, Focal Lengths (H3)
* Bundle Adjustment with Object Space Constraints for Site Modeling
* Canonic Representations for the Geometries of Multiple Projective Views
* Effects of Camera Alignment Errors on Stereoscopic Depth Estimates
* Multiple View Geometry in Computer Vision
* On The Optimization Criteria Used in Two-View Motion Analysis
* Techniques for Calibration of the Scale Factor and Image Center for High Accuracy 3-D Machine Vision Metrology
* Visually Estimating Workpiece Pose in a Robot Hand Using the Feature Points Method
38 for Camera Calibration
Camera Calibration, Distortion
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Lens Distortion, Aberration, Radial Distortion, Internal Parameters (H2)
Camera Calibration, Focal Length
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Zoom Lens Calibration, Focal Lengths (H3)
Camera Calibration, Laser
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Calibration -- LiDAR, Laser Scanner, Depth Sensor, Scanner Error Analysis (H3)
Camera Calibration, Motion
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Robot Based, Servo (H2)
Section: Camera Calibration, Stereo, Robot Based, Movable (H3)
Camera Calibration, Perspective
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Perspective Based, Vanishing Points (H2)
Camera Calibration, Radiometric
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Atmospheric Corrections for Remote Sensing, Satellite and Space Images (H3)
Section: Photometric Calibration, Radiometric Calibration, Spectral Calibration, Color Calibration (H2)
Section: Radiometric Calibration of Remote Sensing, Satellite and Space Images (H3)
Camera Calibration, Robot
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Robot Based, Servo (H2)
Camera Calibration, Stereo
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Stereo, Robot Based, Movable (H3)
Section: Camera Calibration, Stereo (H2)
Camera Fingerprint
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Source Camera Identification, Camera Fingerprint (H3)
Camera Following
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Target Tracking, Active, Camera Following, Real Time Issues, Hardware (H3)
Camera Identification
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Source Camera Identification, Camera Fingerprint (H3)
Camera Motion
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Building mosaics from video using MPEG motion vectors
Camera Networks
Section: Camera Networks for Surveillance (H4)
Section: Hardware, Sensor and Camera Arrangements for Surveillance Systems (H3)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Camera Orientation
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Orientation Computations, Camera Calibration, Interior Orientation, Exterior Orientation (H2)
Camera Pose
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Pose (H2)
Camera, Conical Mirror
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Real-Time Generation of Environmental Map and Obstacle Avoidance Using Omnidirectional Image Sensor with Conic Mirror
Camera, Spherical Mirror
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Feature Matching in 360^o Waveforms for Robot Navigation
* Image-Based Navigation Using 360^o Views
Camera, Variable Focus
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Obtaining Focused Images Using a Non-frontal Imaging Camera
Cameras
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Optical Sensors for Machine Vision (H2)
Section: Sensors for Machine Vision, Image Sensors (H1)
Camouflage
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Camouflaged Object Detection, Camouflage (H3)
Cancelable Fingerprint
Section: Cancelable Fingerprint Template, Recognition, Analysis, Systems (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Cancer Detection
Section: Medical Applications -- Cancer Diagnosis and Analysis (H1)
Section: Medical Applications -- Cervical Cancer Analysis, Ovarian Cancer (H2)
Section: Medical Applications -- Lymph Nodes (H2)
Section: Medical Applications -- Prostate Cancer Analysis (H2)
Section: Medical Applications -- Skin Cancer, Melanoma (H2)
Section: Medical Applications -- Thyroid (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
7 for Cancer Detection
Canny Edges
Section: Directional Masks, Gaussian Masks, Canny etc. (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Canola
Section: Rapeseed Crop Analysis, Canola Analysis, Production, Detection (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Canonical Correlation Analysis
Section: Canonical Correlation Analysis (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Canonical Views
Section: Aspect Graph Matching, Characteristic Views (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Canopy Height
Section: Canopy Height Measurement (H4)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Forest Analysis, Canopy Heights, LiDAR (H4)
Canopy Water
Section: Canopy Water Content (H3)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Canopy
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Trees, Forest Canopy Analysis (H3)
Capsule Network
Section: Capsule Networks (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
CAPTCHA
Section: Completely Automated Public Turing Test to Tell Computers and Humans Apart, CAPTCHA, Generation, Breaking (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Breaking reCAPTCHAs with Unpredictable Collapse: Heuristic Character Segmentation and Recognition
* CAPTCHA Challenge Tradeoffs: Familiarity of Strings versus Degradation of Images
* ScatterType: a legible but hard-to-segment CAPTCHA
Captioning
Section: Captioning, Image Captioning (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Multi-Modal, Cross-Modal Captioning, Image Captioning (H3)
Section: Transformer for Captioning, Image Captioning (H3)
Section: Video Retrieval, Video Annotation, Video Categorization, Genre (H4)
Captions
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Video Analysis -- Captions, Text, Video Text (H3)
Car Following
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Car Following Control, Leader-Follower Control (H4)
Carbon Dioxide
Section: Pollution, CO2 Measurements, Carbon Dioxide, Carbon Monoxide (H4)
Section: Pollution, Greenhouse Gasses (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Carbon Monoxide
Section: Pollution, CO2 Measurements, Carbon Dioxide, Carbon Monoxide (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Carbon Sequestration
Section: Carbon Sequestration, CO2 Sequestration, Carbon Storage (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Carbon Storage
Section: Carbon Sequestration, CO2 Sequestration, Carbon Storage (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Carbon
Section: Carbon Sequestration, CO2 Sequestration, Carbon Storage (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Soil Organic Carbon (H2)
Carciac
Section: Cardiac Electrophysiology (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Cardiac CT
Section: Heart, Cardiac, Angiography using CAT, CT, Tomography (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Cardiac Motion
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Tracking Applied to Heart Images (H3)
Cardiac MRI
Section: Heart, Cardiac Analysis using MRI Analysis, Cardiac MRI (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Cardiac Ultrasound
Section: Heart, Cardiac, Echocardiography, Ultrasound (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Cardiac
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Deformable Models, Cardiac Motion Models for Volumes, Left Ventricle (H3)
Section: Medical Applications -- Heart, Cardiac Applications (H1)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Cargo Inspection
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Surveillance Systems, Applied to Baggage Inspection, Cargo Inspection (H3)
Carotid Artery
Section: Medical Applications -- Coronary Arteries, Carotid Arteries (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Carried Objects
Section: Carried Objects, Carrying Objects (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Cartography
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: CMU MAPS Image Database System (H1)
Section: Evaluation, Quality Assissment Pansharpening (H4)
Section: General Cartography, Remote Sensing Issues (H1)
Section: Image and Sensor Fusion for Cartography and Aerial Images, Satellite Images, Remote Sensing (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Pansharpening, Fusion of Aerial Images (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: SRI General Cartography Systems (H1)
Section: Workshops -- Mapping, Cartography, Urban Models, Remote Sensing (H3)
* Knowledge-Based Aerial Photo Interpretation
* Learning to Detect Rooftops in Aerial Images
* Marco: Map Retrieval by Content
* Rule Based Interpretation of Aerial Imagery
* Semi-Automated Object Measurement Using Multiple-Image Matching from Mobile Mapping Image Sequences
18 for Cartography
Cartoon Segmentation
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cartoon Plus Texture Segmentation, Cartoon-Texture Segmentation (H3)
Cartoons
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Speech Ballons in Comics, Comic Analysis, Panel Detection (H4)
Cascade Classifier
Section: Hierarchical Combination, Multi-Stage Classifiers (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Castings
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Metal Inspection, Castings, Machining (H3)
CAT
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Tomographic Image Generation, CAT, CT, Reconstruction (H2)
Section: Tomographic Images, CAT Scans (Computed Axial Tomography) (H1)
Section: Tomographic Images, CAT, CT, Overviews, Surveys, Datasets (H2)
Section: Tomographic Object Construction, Object Extraction, Analysis, Organs (H2)
Catadioptric Calibration
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Catadioptric, Omnidirectional Camera Calibration, Fisheye Lens (H3)
Catadioptric Camera
Section: Catadioptric Cameras (H4)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Epipolar geometry of catadioptric stereo systems with planar mirrors
Catadioptric
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Catadioptric, Omnidirectional Camera Calibration, Fisheye Lens (H3)
Cataract
Section: Cataracts, Detection, Analysis, Surgery (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Caves
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Specific 3-D Models, Rock Art, Petroglyphs, Rock Structures, Caves (H2)
CBIR
Section: Document Retrieval Systems, Databases and Issues, Libraries (H2)
Section: Image Database -- Overall Systems (H2)
Section: Image Database Applications, Content Based Image Retrieval (H1)
Section: Image Database, Retrieval -- Surveys, Evaluations (H2)
Section: Image Retrieval, Libraries, Databases, Multimedia (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
7 for CBIR
CCA
Definition:* Canonical Correlation Analysis.
Cell Extraction
Section: Extraction and Analysis of Cells (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Cell Nucleus
Section: Cell Nucleus, Cell Nuclei Analysis, Detection (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Cell Phone
Section: Cell Phone Transmission Issues, 5G, 6G (H3)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Cell Segmentation
Section: Extraction and Analysis of Cells (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Cell Tracking
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Tracking Cells, Deformations, Motion, Real-Time Analysis (H3)
Cells
Section: 3-D Cell Analysis (H3)
Section: Blood Cell Cancers, Lymphoma, Leukemia (H3)
Section: Blood Cells, Counting, Extraction, Analysis (H2)
Section: Cell Nucleus, Cell Nuclei Analysis, Detection (H3)
Section: Extraction and Analysis of Cells (H2)
Section: Malaria Detection, Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Surveys, Comparisons, Cells, DNA (H2)
Section: Tracking Cells, Deformations, Motion, Real-Time Analysis (H3)
9 for Cells
Cellular Automata
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Multi-Processor Algorithms, Multi-Core, Cellular, Systolic (H2)
* Parallel Image Processing by Memory-Augmented Cellular Automata
Cellular Based
Section: Cell Based, 6G, 5G, 4G, LTE (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Cellular Networks
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Mobile, Cellular, LTE, Tranmission (H4)
Cerebral Aneurysm
Section: Brain, Cortex, Cerebral Arteries, Cerebral Aneurysm, Cerebrovascular (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Cervical Cancer
Section: Medical Applications -- Cervical Cancer Analysis, Ovarian Cancer (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
CH4
Section: Pollution, Methane Measurements, CH4, Other Hydrocarbons (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Chain Codes
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Chain Code Representations (H3)
Section: Curve Partitions, Applied to Chain Codes (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Chain-Link Compression of Arbitrary Black-White Images
* Chaincode Contour Processing for Handwritten Word Recognition
* On Limit Properties in Digitization Schemes
* On the Encoding of Arbitrary Geometric Configurations
9 for Chain Codes
Chain Codes, Evaluation
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Analysis of the Precision of Generalized Chain Codes for the Representation of Planar Curves
Chain Codes, Survey
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Computer Processing of Line Drawing Images
Challenge Results
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Target Tracking Challenges, Result Summaries (H4)
Chamfer Matching
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Chamfering: A fast method for obtaining approximations of the Euclidean distance in N dimensions
* Fast directional chamfer matching
* Parametric Correspondence and Chamfer Matching: Two New Techniques for Image Matching
Change Detection
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Applied Change Analysis, Specific Site Applications, Site Specific Temporal (H2)
Section: Building Change Detection (H4)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Change Detection -- Image Level (H2)
Section: Change Detection for Damage Assessment (H3)
Section: Change Detection for Hyperspectral Images (H3)
Section: Change Detection for Remote Sensing Image Level (H3)
Section: Change Detection, Urban Area Land Cover, Temporal Analysis (H3)
Section: Changes using Landsat Images (H4)
Section: Erosion Analysis, Changes (H2)
Section: Forest Change Evaluation, Change Detection, Temporal Analysis (H3)
Section: Forest Disturbance, Regeneration, Regrowth (H3)
Section: Forest Storm Damage Assessment, Wind Throw (H4)
Section: Land Cover Change Analysis Using Learning, Neural Nets (H3)
Section: Land Cover Change Analysis, Global Changes, Global Analysis (H3)
Section: Land Cover Change Analysis, Remote Sensing Change Analysis, Temporal Analysis (H2)
Section: Land Cover Change Analysis, Seasonal, Annual Variations, Climate Change, Analysis (H3)
Section: Land Cover Change Analysis, Temporal Analysis, Specific Site, China (H3)
Section: Land Cover, Land Use Change Analysis for Radar and SAR (H4)
Section: Land Use Change Analysis (H3)
Section: Long Term Changes, Climate Change, Analysis (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Misregistration Errors, Evaluation Change Detection (H3)
Section: NDVI, Normalized Difference Vegetation Index, Changes (H3)
Section: Night Time Image Analysis for Urban Area Detection, Change and Growth (H3)
Section: Pasture, Grassland, Rangeland, Change, Degradation, Temporal (H4)
Section: Plant Disease Analysis, General Plant Diseasses (H3)
Section: Point Cloud Change Detection, Registration (H4)
Section: Radar, SAR Image Change Detection (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Shore Line Changes, Erosion (H3)
Section: Site Model Change Detection, Map Update (H3)
Section: Tundra Regions, Permafrost Analysis (H2)
Section: Very High Resolution Land Cover Change Analysis (H3)
* Automatic Comparison of a Topographic Map with Remotely-Sensed Images in a Map Updating Perspective: The Road Network Case
* Change Detection and Analysis in Multi-Spectral Images
* Detecting Changes in Aerial Views of Man-Made Structures
* Fast Structure-Adaptive Evaluation of Local Features in Images, A
* Model Validation for Change Detection
* Optimum Multisensor Data Fusion for Image Change Detection
* Quantitative Measures of Change Based on Feature Organization: Eigenvalues and Eigenvectors
* Segmentation Characterization for Change Detection
* Standardized Radiometric Normalization Method for Change Detection Using Remotely Sensed Imagery, A
* Symbolic Image Registration and Change Detection
47 for Change Detection
Change Detection, Differencing
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Algorithm for Estimating Small Scale Differences Between Two Digital Images, An
* Computer Comparison of Pictures
* Novel Change Detection Algorithm Using Adaptive Threshold, A
* Site-Model-Based Change Detection and Image Registration
* Techniques for Change Detection
7 for Change Detection, Differencing
Character Recognition
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Arabic Numbers, Digits, Handwritten, Numeral Recognition (H3)
Section: Character Recognition Survey, Overview, Evaluations (H2)
Section: Character Recognition Systems (H1)
Section: Chinese Characters, Japanese Characters, Handwritten (H3)
Section: Chinese Characters, Using Stroke and Radical Analysis, Features (H3)
Section: Chinese, Japanese and Kanji Characters (H2)
Section: Documents and Character Analysis -- Surveys, Comparisons, Evaluations (H1)
Section: General Character Recognition Issues (H2)
Section: Hidden Markov Models, HMM (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Multiple Classifiers Applied to Arabic Numbers (H4)
Section: Neural Networks for Numbers and Digits (H4)
Section: OCR Evaluations (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Online Recognition of Chinese Characters (H3)
Section: Other Character Sets (H2)
Section: Roman Alphabet (H2)
* Adaptive Algorithm for Text Detection from Natural Scenes, An
* Fuzzy Pyramid Scheme for Distorted Object Recognition
* Hexagonal Wavelet Representations for Recognizing Complex Annotations
* Image Thresholding for Optical Character Recognition and Other Applications Requiring Character Image Extraction
* Scene Text Extraction and Translation for Handheld Devices
23 for Character Recognition
Characteristic Views
Section: Aspect Graph Matching, Characteristic Views (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Charging Stations
Section: Charging Station Placement, Schedulding, Scaling (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Charging
Section: Charging Station Placement, Schedulding, Scaling (H4)
Section: Electric Vehicle Issues, Usage, Charging, Controls (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Pricing Issues in Charging (H4)
Section: Transit, Bus, Electric Vehicle Issues (H4)
Section: Wireless Power, Wireless Charging (H4)
Check Amounts
Section: Money and Check Processing -- Amounts, etc. (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Chest X-Ray
Section: Chest X-Ray Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Ribs, Chest X-Rays (H3)
Section: Tuberculosis Analysis, Tuberculosis Bacilli (H3)
Chinese Character Recognition
Section: Chinese Characters, Japanese Characters, Handwritten (H3)
Section: Chinese Characters, Review, Survey, Evaluations (H3)
Section: Chinese Characters, Using Stroke and Radical Analysis, Features (H3)
Section: Chinese, Japanese and Kanji Characters (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Online Recognition of Chinese Characters (H3)
Chinese Seal Recognition
Section: Chinese Character Seals (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Chlorophyll Fluorescence
Section: Chlorophyll Estimation, Chlorophyll Concentration, Chlorophyll Fluorescence, Chlorophyll Index (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Chlorophyll
Section: Chlorophyll Estimation in Water (H3)
Section: Chlorophyll Estimation, Chlorophyll Concentration, Chlorophyll Fluorescence, Chlorophyll Index (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Chromosomes
Section: Chromosome Analysis and Extraction, Genome (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Circle Detection
Section: Circular Features, Circle Detection, Circle Fitting, or Particular Curves (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Randomized circle detection with isophotes curvature analysis
Circle Fitting
Section: Circular Features, Circle Detection, Circle Fitting, or Particular Curves (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Circle Generation
Section: Circle Generation (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Circles
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Basic Algorithms to Partition Curves, Represent Curves (H2)
Section: Circle Generation (H3)
Section: Circular Features, Circle Detection, Circle Fitting, or Particular Curves (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Hough Transform -- Circle Features (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Bayesian Method for Fitting Parametric and Nonparametric Models to Noisy Data, A
* Original Approach for Extracting Circular Shapes from Technical Charts, An
9 for Circles
Circular Features
Section: Circle Generation (H3)
Section: Circular Features, Circle Detection, Circle Fitting, or Particular Curves (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Citrus
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Citrus Trees, Orchards, Diseases (H4)
City Models
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Large Scale Models, City Scale Models, City Models (H2)
City
Section: GIS Implementation, City Models, Urban Models, City Data (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
CityGML
Section: CityGML (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Clarity
Section: Coastal Water Quality, Water Clarity (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Water Clarity (H3)
Classifer Combinations
Section: Bagging, Combinations, Classifiers (H4)
Section: Classifier Combination, Evaluation, Overview, Appliction Specific (H4)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Hierarchical Combination, Multi-Stage Classifiers (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Voting for Combinations, Classifiers (H4)
* Multiple classifier combination for face-based identity verification
7 for Classifer Combinations
Classification
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Algal Blooms, Analysis, Detection (H2)
Section: Classification for Crops, Analysis of Production, Specific Crops, Specific Plants (H2)
Section: Classification for Urban Area Land Cover, Remote Sensing (H2)
Section: Classification Methods, Clustering for Region Segmentation (H2)
Section: Clustering Techniques, Pattern Recognition Techniques (H1)
Section: Clustering, Pattern Recognition, General Issues (H2)
Section: Cotton, Analysis and Change (H3)
Section: Cyanobacteria, Analysis, Detection (H3)
Section: Dryland Analysis and Change, Arid Regions (H4)
Section: Feature Selection in Pattern Recognition or Clustering (H2)
Section: Floodplains, Riverside (H3)
Section: Ice Detection, Glaciers Detection and Analysis (H1)
Section: K-Means Clustering (H2)
Section: King Sun Fu Pattern Recognition Papers (H2)
Section: Land Cover Analysis, Specific Location Applications, Site Analysis, Site Specific (H1)
Section: Land Cover Analysis, Specific Site North America (H2)
Section: Land Cover Analysis, Specific Site, China (H2)
Section: Land Cover Analysis, Water Detection, Water Areas, Water Body (H1)
Section: Land Cover Change Analysis Using Learning, Neural Nets (H3)
Section: Land Cover Change Analysis, Remote Sensing Change Analysis, Temporal Analysis (H2)
Section: Land Cover Change Analysis, Seasonal, Annual Variations, Climate Change, Analysis (H3)
Section: Land Cover Change Analysis, Temporal Analysis, Specific Site, China (H3)
Section: Land Cover, General Problems, Remote Sensing (H1)
Section: Land Cover, Land Use Change Analysis for Radar and SAR (H4)
Section: Land Surface Temperature, Remote Sensing (H2)
Section: LiDAR for Land Cover, Laser Scanners for Land Cover, Remote Sensing (H2)
Section: Long Term Changes, Climate Change, Analysis (H4)
Section: Maize or Corn Crop Analysis, Production, Detection, Health, Change (H3)
Section: Marsh, Marsh Detection, Analysis (H3)
Section: Nearest Neighbor Classification (H2)
Section: Neural Networks for Classification and Pattern Recognition (H3)
Section: Other Soil Properties, Remote Sensing (H2)
Section: Pasture, Grassland, Rangeland Analysis (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Peatland, Analysis and Change (H3)
Section: Potato Crop Analysis, Production, Detection, Health, Change (H3)
Section: Projection Learning (H3)
Section: Radar for Land Cover, SAR for Land Cover, Remote Sensing (H2)
Section: Rapeseed Crop Analysis, Canola Analysis, Production, Detection (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Rice Crop Analysis, Production, Detection, Health, Change (H3)
Section: Sentinel-1, -2, -3 for Land Cover, Remote Sensing (H3)
Section: Shore Line Changes, Erosion (H3)
Section: Shore Line Detection, Analysis along Shore Line (H2)
Section: Soil Moisture, SMAP, Soil Moisture Active Passive, Remote Sensing (H2)
Section: Soybean Crop Analysis, Beans, Production, Detection, Health, Change (H3)
Section: Sparse Feature Selection (H3)
Section: Statistical Learning, Clustering, Learning Feature Values (H2)
Section: Sugar Cane Crop Analysis, Production, Detection, Health, Change (H3)
Section: Tidal Areas, Inter-Tidal, Coastal, Wetlands, Wetland Detection, Analysis (H3)
Section: Very High Resolution Land Cover Change Analysis (H3)
Section: Vineyard Analysis, Viticulture, Grapes, Production, Detection, Health, Change (H3)
Section: Water Quality, Water Areas (H2)
Section: Wetlands, Wetland Detection, Analysis (H2)
Section: Wheat Crop Analysis, Detection, Change (H3)
* Performance Evaluation of Multispectral Analysis for Surface Material Classification
57 for Classification
Classification, 3-D Data
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Point Cloud Classification, Recognition (H3)
Classifier Combinations
Section: Fusion for Multiple Classifiers (H4)
Section: Mixture of Experts, Multiple Classifiers, Combining Classifiers (H4)
Section: Multiple Classifiers, Combining Classifiers, Combinations (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Classifier Ensembles
Section: Fusion for Multiple Classifiers (H4)
Section: Mixture of Experts, Multiple Classifiers, Combining Classifiers (H4)
Section: Multiple Classifiers, Combining Classifiers, Combinations (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Classifiers, multiple
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Generalized-Approach to the Recognition of Structurally Similar Handwritten Characters Using Multiple Expert Classifiers
Classroom Environment
Section: Human Action Recognition, Indoor Environments, Classroom, Smart Room (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Climate Change
Section: Climate Data (H2)
Section: Land Cover Change Analysis, Global Changes, Global Analysis (H3)
Section: Land Cover Change Analysis, Seasonal, Annual Variations, Climate Change, Analysis (H3)
Section: Long Term Changes, Climate Change, Analysis (H4)
Section: NDVI, Normalized Difference Vegetation Index, Changes (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Primary Production, an Index of Climate Change in the Ocean: Satellite-Based Estimates over Two Decades
7 for Climate Change
Climate Zones
Section: Climate Zones (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Climate
Section: Climate Data (H2)
Section: Land Cover Change Analysis, Seasonal, Annual Variations, Climate Change, Analysis (H3)
Section: Long Term Changes, Climate Change, Analysis (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
CLIP
Section: CLIP, Contrastive Language-Image Pre-Training (H4)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Clock Drift
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: GPS, GNSS Network, Bias, Clock Drift (H4)
Close Range Photogrammetry
Section: Automated Measurement Systems, Close Range Photogrammetry (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Closest Point
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Closest Point Algorithms, ICP, Iterative Closest Point (H3)
Cloth Changing
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Re-Identification, Cloth-Changing, Clothes Changing (H4)
Cloth Rendering
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Rendering, Cloth, Clothing, Fabric (H4)
Clothes
Section: Clothing Styles, Fashion Related (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Human Posture and Shape, Clothing Related (H3)
Clothing Changing
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Re-Identification, Cloth-Changing, Clothes Changing (H4)
Clothing
Section: Clothing Try-On Systems (H4)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Cloud Detection
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cloud Detection, Extraction and Removal (H2)
Section: Cloud Detection, Ground-Based (H3)
Section: Cloud Shadows, Combined Cloud and Shadow, Extraction and Removal (H2)
Section: Thin Cloud Detection and Removal (H3)
Cloud Identification
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cloud Identification, Cloud Type, Cloud Properties (H3)
Cloud Removal
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cloud Detection, Extraction and Removal (H2)
Cloud Shadow
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cloud Shadows, Combined Cloud and Shadow, Extraction and Removal (H2)
Cloud Top Height
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cloud Top Heights, Cloud-Top Analysis (H3)
Clouds
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Convective Storm Analysis, Weather Radar Applications (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Optical Flow Field Computations and Use (H)
Section: Tracking for Weather, Clouds (H3)
* Correlation-Relaxation-Labeling Framework for Computing Optical Flow: Template Matching from a New Perspective, A
Clumping Index
Section: Clumping Index, Measurement, Effects (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Clustering
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Binary Clustering, Two Class Classification (H3)
Section: Classification Methods, Clustering for Region Segmentation (H2)
Section: Clustering Applications (H2)
Section: Clustering Techniques, Pattern Recognition Techniques (H1)
Section: Clustering, Classification, General Methods (H2)
Section: Clustering, Pattern Recognition, General Issues (H2)
Section: Density Based Clustering (H3)
Section: Detecting Clusters and Number of Clusters, Number of Classes (H2)
Section: Fuzzy Clustering, Cluster Validity Tests (H3)
Section: Fuzzy Clustering, Fuzzy Classification Techniques, Fuzzy C-Means (H2)
Section: Fuzzy Clustering, Overview, Summary, Comparisons (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Linear Separable Classification (H2)
Section: One Class Clustering, One Class Classification (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Unsupervised Clustering and Optimal Clusters for Segmentation (H3)
* Bottom Up Image Segmentor, A
* Image Segmentation by a Parallel, Non-Parametric Histogram Based Clustering Algorithm
* On Threshold Selection Using Clustering Criteria
* Parallel Hierarchical-Clustering Algorithms on Processor Arrays with a Reconfigurable Bus System
* Recursive Clustering Technique for Color Picture Segmentation, A
22 for Clustering
Clustering, Hierarchical
Section: Iterative, Hierarchical Clustering Techniques (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Clustering, Iterative
Section: Iterative, Hierarchical Clustering Techniques (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Clusters Detection
Section: Detecting Clusters and Number of Clusters, Number of Classes (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Clutter
Section: ATR -- Clutter, Background Issues, Noise (H2)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Target Tracking Techniques, Occlusions, Clutter (H4)
* Ratio of the Arithmetic to the Geometric Mean: A First-order Statistical Test for Multilook SAR Image Homogeneity, The
CME
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: SRI Environments -- Image Calc, CME RADIUS (H2)
CNN
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Convolutional Neural Network, CNN, Re-Identification Issues, Pedestrian Tracking (H4)
Section: Convolutional Neural Networks for Human Action Recognition and Detection (H4)
Section: Convolutional Neural Networks for Image Descriptions, Classification (H3)
Section: Convolutional Neural Networks for Object Detection and Segmentation (H4)
Section: Convolutional Neural Networks for Semantic Segmentation, CNN (H4)
Section: Convolutional Neural Networks, Design, Implementation Issues (H4)
Section: Deep Networks, Deep Learning for Human Action Recognition (H4)
Section: Efficient Implementations Convolutional Neural Networks (H4)
Section: Face Recognition Systems Using Neural Networks, Learning (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Fine-Grained Classification Using CNN, Convolutional Neural Networks (H4)
Section: Forgetting, Learning without Forgetting, Convolutional Neural Networks (H4)
Section: Human Posture, or Human Pose, Learning, Neural Networks (H3)
Section: Hyperspectral Data, Neural Networks for Classification (H4)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Incremental Learning for Human Action Recognition (H4)
Section: Inpainting, GAN, CNN, Neural Nets, Learning (H4)
Section: Intrepretation, Explaination, Understanding of Convolutional Neural Networks (H4)
Section: Learning, General Surveys, Overviews (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Neural Net Compression (H4)
Section: Neural Net Pruning (H4)
Section: Neural Net Quantization (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Point Cloud Processing for Neural Networks, Convolutional Neural Networks (H3)
Section: Pooling in Convolutional Neural Networks Implementations (H4)
Section: Salient Regions, Convolutional Neural Networks, Deep Nets (H4)
Section: Single View 3D Reconstruction, Convolutional Neural Networks, CNN (H3)
Section: Single View 3D Reconstruction, Learning (H3)
Section: VQA, Visual Question Answering, Neural Networks (H4)
35 for CNN
Co-Clustering
Section: Multi-View Learning, Co-Clustering (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Co-occurrence Matrix
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Co-occurrence Matrix Description Methods (H1)
* Optical Texture Analysis for Automatic Cytology and Histology: A Markovian Approach
* Statistical-Methods to Compare the Texture Features of Machined Surfaces
* Textural Features for Image Classification
Co-Salient
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Co-Salient Detection (H3)
Co-Segmentation
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Co-Segmentation, Cosegmentation (H2)
CO2
Section: Carbon Sequestration, CO2 Sequestration, Carbon Storage (H3)
Section: Pollution, CO2 Measurements, Carbon Dioxide, Carbon Monoxide (H4)
Section: Pollution, Greenhouse Gasses (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Coast
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Shore Line Changes, Erosion (H3)
Coastal Analysis
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Coastal, Tidal Flood Analysis, Storm Surge (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Shore Line Detection, Analysis along Shore Line (H2)
Section: Tsunami Detection, Analysis, Warning, Disaster (H4)
Coastal
Section: Coastal Water Quality, Water Clarity (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Tidal Areas, Inter-Tidal, Coastal, Wetlands, Wetland Detection, Analysis (H3)
Code Convolutional Networks
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Sequentially Aggregated Convolutional Networks
Code LPB-TOP
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* LBP-TOP: A Tensor Unfolding Revisit
Code, 3-D Segmentation
* *Seg3D: Volumetric Image Segmentation and Visualization
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Code, 3-D Shape
* *AQSENSE
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Code, 3-D Visualization
* *map3d: Interactive scientific visualization tool for bioengineering data
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Code, 3D Data
* *libE57: software tools for managing E57 files
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Code, 3D Fly Through
* *Make3D
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Code, 3D Reconstruction
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Analysis and Implementation of a Parallel Ball Pivoting Algorithm, An
Code, 3D Vision
Section: Books, Collections, Overviews, General, and Surveys (H)
* Guide to 3D Vision Computation: Geometric Analysis and Implementation
Code, 3D
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Optical Flow Field Computations and Use (H)
* Deep Meta Functionals for Shape Representation
* Order-Aware Generative Modeling Using the 3D-Craft Dataset
* PointFlow: 3D Point Cloud Generation With Continuous Normalizing Flows
Code, Action Recognition
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* CoTeRe-net: Discovering Collaborative Ternary Relations in Videos
* EAN: Event Adaptive Network for Enhanced Action Recognition
* Motion-Driven Visual Tempo Learning for Video-Based Action Recognition
* TCGL: Temporal Contrastive Graph for Self-Supervised Video Representation Learning
* Win-Fail Action Recognition
7 for Code, Action Recognition
Code, Active Appearance Model
* *AAM Building
* *Active Appearance Models
* *am_tools
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Code, Active Blobs
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Active Blobs
Code, Active Contours
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Segmentation with Active Contours
Code, Adversarial Attack
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Spatiotemporal Attacks for Embodied Agents
Code, Affine Invariant
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* CNN-Assisted Coverings in the Space of Tilts: Best Affine Invariant Performances with the Speed of CNNs
Code, Affine Shape
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Repeatability Is Not Enough: Learning Affine Regions via Discriminability
Code, Alignment
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Cross-Domain Detection via Graph-Induced Prototype Alignment
* Fast, Approximately Optimal Solutions for Single and Dynamic MRFs
Code, Annotation
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Generating Easy-to-Understand Referring Expressions for Target Identifications
* LableMe: The Open Annotation Tool
Code, Anomaly Detection
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Graph Laplacian for image anomaly detection
* How to Reduce Anomaly Detection in Images to Anomaly Detection in Noise
Code, Artistic
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Learning to Paint With Model-Based Deep Reinforcement Learning
Code, Attention
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* MixFormer: Mixing Features across Windows and Dimensions
* Stand-Alone Inter-Frame Attention in Video Models
Code, AVU
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Open-Source Platform for Underwater Image and Video Analytics, An
Code, B-Spline
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Optimization of Image B-spline Interpolation for GPU Architectures
Code, Bilateral Filter
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Bilateral Filter for Point Clouds, The
Code, Blur
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Estimating an Image's Blur Kernel Using Natural Image Statistics, and Deblurring it: An Analysis of the Goldstein-Fattal Method
Code, Brain Lesion Segmentation
* *brain lesion segmentation
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Code, Bundle Adjustment
* *Simple Sparse Bundle Adjustment (SSBA)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Addingham Bundle Adjustment
* Apero, An Open Source Bundle Adjusment Software For Automatic Calibration and Orientation of Set of Images
* Design and Implementation of a Generic Sparse Bundle Adjustment Software Package Based on the Levenberg-Marquardt Algorithm, The
* Generic Bundle Adjustment Methodology for Indirect RPC Model Refinement of Satellite Imagery, A
Code, CAD
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Neural Face Identification in a 2D Wireframe Projection of a Manifold Object
Code, Calibration
* *HySCaS: Hybrid Stereoscopic Calibration Software
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Code, Camera Calibration
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Flexible New Technique for Camera Calibration, A
* Matlab Camera Calibration Toolbox
* Versatile Camera Calibration Technique for High-Accuracy 3D Machine Vision Metrology Using Off-the-Shelf TV Cameras and Lenses, A
Code, Captioning
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Attention on Attention for Image Captioning
* Cap2Det: Learning to Amplify Weak Caption Supervision for Object Detection
* Controllable Video Captioning With POS Sequence Guidance Based on Gated Fusion Network
* Human Attention in Image Captioning: Dataset and Analysis
Code, Chain Code
* *Chain Code Representation
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Fast Chain Coding of Region Boundaries
Code, Chain Code, C
* *Chain Code Representation
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Code, Change Detection
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Detection and Interpretation of Change in Registered Satellite Image Time Series
* Image Difference Captioning With Instance-Level Fine-Grained Feature Representation
Code, Classification
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Boosting Standard Classification Architectures Through a Ranking Regularizer
* Label Relation Graphs Enhanced Hierarchical Residual Network for Hierarchical Multi-Granularity Classification
* Region-based Non-local Operation for Video Classification
* Scan: Learning to Classify Images Without Labels
* Spatially Consistent Representation Learning
7 for Code, Classification
Code, Cloud Detection
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Cloud Detection by Luminance and Inter-band Parallax Analysis for Pushbroom Satellite Imagers
Code, Clustering
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Optimized Data Fusion for Kernel k-Means Clustering
Code, CNN
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Convolution of Convolution: Let Kernels Spatially Collaborate
* Learning to Learn Parameterized Classification Networks for Scalable Input Images
* Null-sampling for Interpretable and Fair Representations
* PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer
* Reduced Biquaternion Convolutional Neural Network for Color Image Processing
Code, Color Balance
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Simplest Color Balance
Code, Color Correction
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Local Color Correction
Code, Color Descriptors
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Evaluating Color Descriptors for Object and Scene Recognition
Code, Color Enhancement
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Algorithmic Analysis of Variational Models for Perceptual Local Contrast Enhancement, An
* Automatic Color Enhancement (ACE) and its Fast Implementation
Code, Color Histograms
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Image Color Cube Dimensional Filtering and Visualization
Code, Colorization
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* DeOldify: A Review and Implementation of an Automatic Colorization Method
Code, Compression
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Deep Image Compression Using Decoder Side Information
Code, Computational Geometry
* *CGAL: Computational Geometry Algorithms Library
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Code, Computer Vision
* *AccelerEyes
* *FastCV
* *Fiji Image Processing Package
* *GPU4Vision
* *Handbook of Computer Vision and Applications. 3. Systems and Applications
* *OpenCV
* *OpenVidia
* *PEIPA Computer Vision Software
* *VXL
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Computer Vision and Applications: A Guide for Students and Practitioners
* Handbook of Mathematical Models in Computer Vision
* Invitation to 3-D Vision: From Images to Geometric Models, An
* MATLAB and Octave Functions Software for Computer Vision and Image Processing
* Practical Computer Vision Using C
* Robotics, Vision and Control: Fundamental Algorithms in MATLAB
17 for Code, Computer Vision
Code, Computer Vision, C++
* *VXL
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Code, Computer Vision, Matlab
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* MATLAB and Octave Functions Software for Computer Vision and Image Processing
* Robotics, Vision and Control: Fundamental Algorithms in MATLAB
Code, Connected Components
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Extraction of Connected Region Boundary in Multidimensional Images
Code, Contours
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Meaningful Scales Detection: An Unsupervised Noise Detection Algorithm for Digital Contours
Code, Contrast Enhancement
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Local Contrast Enhancement based on Adaptive Logarithmic Mappings
Code, Contrastive Learning
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Video-Text Representation Learning via Differentiable Weak Temporal Alignment
Code, Convex Grouping
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Robust and Efficient Detection of Salient Convex Groups
Code, Convex Hull
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Exact polyhedral visual hulls
Code, ConvNet
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* MutualNet: Adaptive Convnet via Mutual Learning from Network Width and Resolution
Code, Convolutional Networks
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* CARAFE: Content-Aware ReAssembly of FEatures
* Dynamic Block Sparse Reparameterization of Convolutional Neural Networks
* Perspective-Guided Convolution Networks for Crowd Counting
* Simple and Robust Deep Convolutional Approach to Blind Image Denoising, A
8 for Code, Convolutional Networks
Code, Convolutional Neural Nets
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions
Code, Convolutional Neural Networks
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Approximated Bilinear Modules for Temporal Modeling
* BAE-NET: Branched Autoencoder for Shape Co-Segmentation
* Convolutional Character Networks
* Learning Filter Basis for Convolutional Neural Network Compression
* Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis
* Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection
11 for Code, Convolutional Neural Networks
Code, Corner Detection
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Analysis and Implementation of the Harris Corner Detector, An
Code, Correlation
* 117 Line 2D Digital Image Correlation Code Written in MATLAB, A
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Code, Counting
* 3C-Net: Category Count and Center Loss for Weakly-Supervised Action Localization
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Counting With Focus for Free
* From Open Set to Closed Set: Counting Objects by Spatial Divide-and-Conquer
* Learning To Count Everything
7 for Code, Counting
Code, Crack Detection
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* All Terrain Crack Detector Obtained by Deep Learning on Available Databases, An
* Crack Segmentation on UAS-based Imagery using Transfer Learning
Code, CT Data Analysis
* *Core Imaging Library (CIL)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Code, CT
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Core Imaging Library - Part I: a versatile Python framework for tomographic imaging
* Core Imaging Library - Part II: multichannel reconstruction for dynamic and spectral tomography
* Musiré: multimodal simulation and reconstruction framework for the radiological imaging sciences
Code, Curvature
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Image Curvature Microscope: Accurate Curvature Computation at Subpixel Resolution, The
Code, Curve Decomposition
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Digital Level Layers for Digital Curve Decomposition and Vectorization
Code, Curve Detection
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* TriplClust: An Algorithm for Curve Detection in 3D Point Clouds
Code, Curve Partitions
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Near-Linear Time Guaranteed Algorithm for Digital Curve Simplification Under the Fréchet Distance, A
Code, Curve Segmentation
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Nonparametric Segmentation of Curves into Various Representations
Code, Curve Smoothing
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Algorithm for 3D Curve Smoothing, An
* Non-Parametric Multi-Scale Curve Smoothing
Code, Curvilinear Structures
* 2D Filtering of Curvilinear Structures by Ranking the Orientation Responses of Path Operators (RORPO)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Code, Deblurring
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Breaking down Polyblur: Fast Blind Correction of Small Anisotropic Blurs
* Spectral Pre-Adaptation for Restoring Real-World Blurred Images using Standard Deconvolution Methods
Code, Deehazing
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Dehazing with Dark Channel Prior: Analysis and Implementation
Code, Deep Learning
* *Open Deep Learning Toolkit for Robotics (OpenDR)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Defensive Patches for Robust Recognition in the Physical World
* FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
Code, Deep Nets
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Attribution in Scale and Space
Code, Demosaicking
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Fast C++ Implementation of Neural Network Backpropagation Training Algorithm: Application to Bayesian Optimal Image Demosaicing, A
* Gunturk-Altunbasak-Mersereau Alternating Projections Image Demosaicking
* HighEr-Resolution Network for Image Demosaicing and Enhancing
* Image Demosaicking with Contour Stencils
* Malvar-He-Cutler Linear Image Demosaicking
* Self-Similarity Driven Demosaicking
* Zhang-Wu Directional LMMSE Image Demosaicking
8 for Code, Demosaicking
Code, Denoising
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Analysis and Extension of the PCA Method, Estimating a Noise Curve from a Single Image
* Analysis and Extension of the Percentile Method, Estimating a Noise Curve from a Single Image
* Analysis and Implementation of the BM3D Image Denoising Method, Image Processing, An
* Analysis and Improvement of the BLS-GSM Denoising Method, An
* Chambolle's Projection Algorithm for Total Variation Denoising
* DCT image denoising: a simple and effective image denoising algorithm
* Fully Convolutional Pixel Adaptive Image Denoiser
* implementation and detailed analysis of the K-SVD image denoising algorithm, An
* Implementation of a Denoising Algorithm Based on High-Order Singular Value Decomposition of Tensors
* Implementation of Image Denoising based on Backward Stochastic Differential Equations
* Noise Clinic: a Blind Image Denoising Algorithm, The
* Non-local Means Denoising
15 for Code, Denoising
Code, Depth Denoising
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Self-Supervised Deep Depth Denoising
Code, Depth from Focus
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Rational Filters for Passive Depth from Defocus
Code, Depth from Motion
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Exploiting Temporal Consistency for Real-Time Video Depth Estimation
Code, Dermatology
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Joint Acne Image Grading and Counting via Label Distribution Learning
Code, Detection Transformer
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Accelerating DETR Convergence via Semantic-Aligned Matching
Code, Distance Transform
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Distance Transforms of Sampled Functions
* Streaming Distance Transform Algorithm for Neighborhood-Sequence Distances, A
Code, Distortion Correction
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Automatic Lens Distortion Correction Using One-Parameter Division Models
Code, DNN
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Deep Decomposition Learning for Inverse Imaging Problems
Code, Document Analysis
* *Gamera project
Section: OCR, Document Analysis and Character Recognition Systems (H)
* SCRIBO Module of the Olena Platform: A Free Software Framework for Document Image Analysis, The
Code, Domain Adaption
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Domain Adaptation for Semantic Segmentation With Maximum Squares Loss
* Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation
* Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation
* Semi-Supervised Domain Adaptation via Minimax Entropy
* Temporal Attentive Alignment for Large-Scale Video Domain Adaptation
Code, Domain Generalization
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Study of RobustNet, a Domain Generalization Method for Semantic Segmentation, A
Code, Drone Control
* *Flightmare
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Learning High-Speed Flight in the Wild
Code, Drones
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Deep Drone Acrobatics
Code, Edge Detection
* *Edison: Edge Detection and Image SegmentatiON system
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Combined Corner and Edge Detector, A
* Contours, Corners and T-Junctions Detection Algorithm
* Global Measures of Coherence for Edge Detector Evaluation
* Logical/Linear Operators for Image Curves
* Recursive Filtering and Edge Tracking: Two Primary Tools for 3D Edge Detection
* Structured edge detection toolbox
* Susan: A New Approach to Low-Level Image-Processing
* Unsupervised Smooth Contour Detection
11 for Code, Edge Detection
Code, Egocentric Actions
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* What Would You Expect? Anticipating Egocentric Actions With Rolling-Unrolling LSTMs and Modality Attention
Code, Ellipse Fitting
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Ellipse Fitting for Computer Vision: Implementation and Applications
* Ellipse-Specific Direct Least-Square Fitting
Code, Emotion Analysis
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* MixedEmotions: An Open-Source Toolbox for Multimodal Emotion Analysis
Code, Energy Minimization
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Computing geodesics and minimal surfaces via graph cuts
Code, Epidemic Model
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Compartmental Epidemiological Model Applied to the Covid-19 Epidemic, A
Code, Equalization
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Non-uniformity Correction of Infrared Images by Midway Equalization
Code, Evaluation
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Learning to Evaluate Perception Models Using Planner-Centric Metrics
Code, Event Camera
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Video to Events: Recycling Video Datasets for Event Cameras
Code, Events
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Bridging the Gap between Events and Frames through Unsupervised Domain Adaptation
Code, Explaination
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations
Code, Eye Fixation
* *PeyeMMV.
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Code, Eye Tracking
* *openEyes
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Code, Face Analysis
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Capturing facial videos with Kinect 2.0: A multithreaded open source tool and database
* OpenFace 2.0: Facial Behavior Analysis Toolkit
* OpenFace: An open source facial behavior analysis toolkit
Code, Face Detection
* *Face Detection Home Page
* *TLD: Tracks the object, Learns its appearance and Detects
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Analysis of the Viola-Jones Face Detection Algorithm, An
* Contrario Detection of Faces with a Short Cascade of Classifiers, A
Code, Face Recognition
* *Face Recogniton Home Page
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* CSU Face Identification Evaluation System: Its purpose, features, and structure, The
* FaRE: Open Source Face Recognition Performance Evaluation Package
* SeqFace: Learning discriminative features by using face sequences
* VarGFaceNet: An Efficient Variable Group Convolutional Neural Network for Lightweight Face Recognition
Code, Face Relighting
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Face Inverse Rendering via Hierarchical Decoupling
Code, Face Tracking
* *TLD: Tracks the object, Learns its appearance and Detects
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Code, Facial Expressions
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* AFFDEX 2.0: A Real-Time Facial Expression Analysis Toolkit
* Computer Expression Recognition Toolbox
* computer expression recognition toolbox (CERT), The
Code, Facial Landmarks
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Aggregation via Separation: Boosting Facial Landmark Detector With Semi-Supervised Style Translation
* FAB: A Robust Facial Landmark Detection Framework for Motion-Blurred Videos
Code, FastICA
* *FastICA package for MATLAB, The
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Code, Feature Selection
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Joint Group Feature Selection and Discriminative Filter Learning for Robust Visual Object Tracking
Code, Feature Tracking
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* IntraFace
Code, Filters
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* How to Apply a Filter Defined in the Frequency Domain by a Continuous Function
Code, Flutter Shutter
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Flutter Shutter Camera Simulator, The
* Flutter Shutter Code Calculator, The
Code, Forensic Similarity
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Forensic Similarity for Source Camera Model Comparison
Code, Forensics, JPEG
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Reliable JPEG Quantization Table Estimator, A
Code, Forgery Detection
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Automatic Detection of Internal Copy-Move Forgeries in Images
Code, Forgery
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Image Forgery Detection via Forensic Similarity Graphs
Code, Fourier
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Shape Discrimination Using Fourier Descriptors
Code, Frame Interpolation
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Time Lens: Event-based Video Frame Interpolation
Code, Fundamental Matrix
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Fundamental Matrix of a Stereo Pair, with A Contrario Elimination of Outliers
Code, Fusion
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Structural Similarity Metrics for Quality Image Fusion Assessment: Algorithms
Code, Fusion, Matlab
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Structural Similarity Metrics for Quality Image Fusion Assessment: Algorithms
Code, Gait
* *Baseline Algorithm and Performance for Gait Based Human ID Challenge Problem
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Code, GAN
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Transforming and Projecting Images into Class-conditional Generative Networks
Code, Gaussian Convolution
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Computing an Exact Gaussian Scale-Space
* Survey of Gaussian Convolution Algorithms, A
Code, Gaze
* *OnMapGaze: A new gaze dataset for map perception modeling
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Few-Shot Adaptive Gaze Estimation
* Gaze360: Physically Unconstrained Gaze Estimation in the Wild
Code, Generative Adversarial Network
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* AutoGAN: Neural Architecture Search for Generative Adversarial Networks
Code, Generative Adversarial Networks
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization
Code, Geospatial Data
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* pyjeo: A Python Package for the Analysis of Geospatial Data
Code, Geospatial
* *OSGeo: Open Source Geospatial Foundation
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Code, Gesture
* *HandVu Gesture Interface
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Code, GIS
* *OSGeo: Open Source Geospatial Foundation
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Code, GNN
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* AEGNN: Asynchronous Event-based Graph Neural Networks
Code, GPU
* *AccelerEyes
* *GPU4Vision
* *OpenVidia
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Code, Graph Embedding
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Deep Clustering by Gaussian Mixture Variational Autoencoders With Graph Embedding
Code, Graph Kernel
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* graphkit-learn: A Python library for graph kernels based on linear patterns
Code, Graph Matching
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Learning Structural Similarity of User Interface Layouts Using Graph Networks
Code, Graph Representation
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Language-Conditioned Graph Networks for Relational Reasoning
* Learning Semantic-Specific Graph Representation for Multi-Label Image Recognition
Code, Ground Visibility
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Ground Visibility in Satellite Optical Time Series Based on A Contrario Local Image Matching
* Temporal Repetition Detector for Time Series of Spectrally Limited Satellite Imagers
Code, H.264/AVC
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* H.264/AVC Refrence Software
Code, Hand Detection
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Contextual Attention for Hand Detection in the Wild
Code, HCI
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* HCI-lambda-2 Workbench: A development tool for multimodal human-computer interaction systems
Code, HDR
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Events-To-Video: Bringing Modern Computer Vision to Event Cameras
* Obtaining High Quality Photographs of Paintings by Image Fusion
Code, Head Tracking
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Fast, Reliable Head Tracking under Varying Illumination: An Approach Based on Registration of Textured-Mapped 3D Models
Code, HEIV
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* HEIV based estimation
Code, High Dynamic Range
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Analysis and Implementation of the HDR+ Burst Denoising Method, An
* Implementation of the Exposure Fusion Algorithm, An
Code, Histogram Modification
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Analysis and Implementation of the Shape Preserving Local Histogram Modification Algorithm, An
Code, Homography
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Iterative Deep Homography Estimation
Code, Hough Transform
* *Hough Transform Code
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Iterative Hough Transform for Line Detection in 3D Point Clouds
Code, Hough Transform, C
* *Hough Transform Code
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Code, HRI
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Top-1 Corsmal Challenge 2020 Submission: Filling Mass Estimation Using Multi-modal Observations of Human-robot Handovers
Code, Human Action
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* BABEL: Bodies, Action and Behavior with English Labels
Code, Human Motion
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Learning Trajectory Dependencies for Human Motion Prediction
* Predicting 3D Human Dynamics From Video
* Structured Prediction Helps 3D Human Motion Modelling
Code, Human Pose
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Learning to Reconstruct 3D Human Pose and Shape via Model-Fitting in the Loop
* Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking
* Resolving 3D Human Pose Ambiguities With 3D Scene Constraints
* Single-Network Whole-Body Pose Estimation
* Tilting at windmills: Data augmentation for deep pose estimation does not help with occlusions
Code, Hyperspectral Classification
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Hyperspectral Image Classification Using Graph Clustering Methods
Code, Illumination Estimation
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Estimating natural illumination from a single outdoor image
Code, Illumination
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Camera parameters estimation from hand-labelled sun positions in image sequences
Code, Image Analysis
* *C++ Template Image Processing Library
* *Core Imaging Library (CIL)
* *Delft Image Processing library, The
* *Image Processing Library 98
* *ImageLib: An Image Processing C++ Class Library
* *LibCVD: computer vision library
* *Microsoft Kinect SDK
* *MPEG Org Home Page
* *NeatVision
* *Noesis Vision
* *Recognition And Vision Library
* *Robot Vision 2 Inc.
* *Torch3vision: Machine Vision Library
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Computational strategies for protein quantitation in 2D electrophoresis gel image processor for Matlab
* Vista: A Software Environment for Computer Vision Research
18 for Code, Image Analysis
Code, Image Analysis, C
* *Delft Image Processing library, The
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Code, Image Analysis, Matlab
* *Delft Image Processing library, The
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Code, Image Coding
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Java-Based MPEG-4 Like Video Codec, A
Code, Image Coding, Java
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Java-Based MPEG-4 Like Video Codec, A
Code, Image Compression
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Compression Method for Arbitrary Precision Floating-Point Images, A
Code, Image Decomposition
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Cartoon + Texture Image Decomposition by the TV-L1 Model
Code, Image Decompostiong
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Directional Filters for Cartoon + Texture Image Decomposition
Code, Image Editing
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction
Code, Image Equalization
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Implementation of the Midway Image Equalization
* Midway Video Equalization
Code, Image Interpolation
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Image Interpolation with Contour Stencils
* Image Interpolation with Geometric Contour Stencils
* Linear Methods for Image Interpolation
* Roussos-Maragos Tensor-Driven Diffusion for Image Interpolation
Code, Image Matching
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Fast Affine Invariant Image Matching
Code, Image Processing
* *AccuSoft
* *Bioimage Suite
* *DgiStreammer
* *FastCV
* *Fiji Image Processing Package
* *Generic Programming for Computer Vision: The VIGRA Computer Vision Library
* *GNU Image Manipulation Program
* *Groningen Image Processing System, GIPSY
* *Handbook of Mathematical Methods in Computer Vision
* *HIPR2: Free WWW-based Image Processing Teaching Materials with JAVA
* *IFS: Image File System
* *Image Processing Online
* *ImageJ-Plugins -- Various Plugins for the image manipulation software ImageJ
* *ImageJ: Image Processing and Analysis in Java
* *ImageMagick
* *IrfanView
* *JPEG 2000
* *JPEG: Joint Photographic Experts Group
* *LibTIFF: TIFF Library and Utilities
* *LTI-Lib
* *MediaCybernetics
* *Mimas
* *Mobile Robot Programming Toolkit, The
* *OpenCV
* *pbmplus Image File Format Conversion Package
* *QCV
* *Supercomputing Systems: Vision
* *Walrus Vision Toolbox
* 3-D Image Processing Algorithms
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Algorithms for Graphics and Image Processing
* Algorithms for Image Processing and Computer Vision
* Building Imaging Applications with Java(TM)
* Computer Vision and Image Processing: A Practical Approach Using CVIPtools
* Concise Introduction to Image Processing using C++, A
* Data Structures for Image Processing in C
* Digital Image Processing Algorithms and Applications
* Digital Image Processing and Analysis: Human and Computer Vision Applications with CVIPtools, Second Edition
* Digital Image Processing Using MATLAB(R), 2nd Edition
* Digital Image Processing: A Practical Introduction Using Java
* Digital Image Processing: An Algorithmic Approach Using Java
* Digital Image Processing: An Algorithmic Approach with MATLAB
* Digital Signal and Image Processing Using MATLAB(R)
* Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab
* Fuzzy Image Processing and Applications with MATLAB
* Handbook of Astronomical Image Processing
* Handbook of Computer Vision Algorithms in Image Algebra
* Handbook of Image Processing Operators
* High Performance Computer Imaging
* HIPS: A Unix-Based Image Processing System
* Hypermedia Image Processing Reference
* Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL
* Image Processing Handbook, The
* Image Processing in Java
* Image Processing with MATLAB: Applications in Medicine and Biology
* Image Processing, Analysis and and Machine Vision: A MATLAB Companion
* Introduction to Image Processing Using R: Learning by Examples
* Machine Vision Algorithms in Java: Techniques and Implementation
* Pattern Recognition and Image Processing in C++
* Photo-Based 3D Graphics in C++: Compositing, Warping, Morphing, and Other Digital Special Effects
* PIKS Foundation C Programmer's Guide
* Practical Algorithms for Image Analysis: Description, Examples, and Code
* Practical Image Processing in C
* Principles of Digital Image Processing: Core Algorithms
* Principles of Digital Image Processing: Fundamental Techniques
* VIPS: A Digital Image Processing Algorithm Development Environment
69 for Code, Image Processing
Code, Image Processing, C
* *FastCV
* *OpenCV
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Data Structures for Image Processing in C
* High Performance Computer Imaging
* Numerical Recipes in C: The Art of Scientific Computing
* PIKS Foundation C Programmer's Guide
* Practical Computer Vision Using C
* Practical Image Processing in C
* Signal Processing Algorithms in Fortran and C
11 for Code, Image Processing, C
Code, Image Processing, C++
* *C++ Template Image Processing Library
* *Generic Programming for Computer Vision: The VIGRA Computer Vision Library
* *Image Processing Library 98
* *ImageLib: An Image Processing C++ Class Library
* *LibCVD: computer vision library
* *LTI-Lib
* *Mimas
* *Mobile Robot Programming Toolkit, The
* *QCV
* *Recognition And Vision Library
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Concise Introduction to Image Processing using C++, A
* Pattern Recognition and Image Processing in C++
* Photo-Based 3D Graphics in C++: Compositing, Warping, Morphing, and Other Digital Special Effects
15 for Code, Image Processing, C++
Code, Image Processing, Java
* *Fiji Image Processing Package
* *HIPR2: Free WWW-based Image Processing Teaching Materials with JAVA
* *ImageJ-Plugins -- Various Plugins for the image manipulation software ImageJ
* *ImageJ: Image Processing and Analysis in Java
* *NeatVision
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Building Imaging Applications with Java(TM)
* Digital Image Processing: A Practical Introduction Using Java
* Digital Image Processing: An Algorithmic Approach Using Java
* Image Processing in Java
* Machine Vision Algorithms in Java: Techniques and Implementation
* Principles of Digital Image Processing: Core Algorithms
* Principles of Digital Image Processing: Fundamental Techniques
14 for Code, Image Processing, Java
Code, Image Processing, Matlab
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Applied Medical Image Processing: A Basic Course
* Circular and Linear Regression: Fitting Circles and Lines by Least Squares
* Digital Image Processing Using MATLAB(R), 2nd Edition
* Digital Image Processing: An Algorithmic Approach with MATLAB
* Digital Signal and Image Processing Using MATLAB(R)
* Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab
* Fuzzy Image Processing and Applications with MATLAB
* Image Processing with MATLAB: Applications in Medicine and Biology
* Image Processing, Analysis and and Machine Vision: A MATLAB Companion
* Signal Processing Algorithms in MATLAB
13 for Code, Image Processing, Matlab
Code, Image Processing, Octave
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Applied Medical Image Processing: A Basic Course
Code, Image Pyramids
* *Zoom It, Seadragon
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Code, Image Recognition
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Funnel Activation for Visual Recognition
Code, Image Registration
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Automatic Homographic Registration of a Pair of Images, with A Contrario Elimination of Outliers
Code, Image Restoration
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* CFSNet: Toward a Controllable Feature Space for Image Restoration
* ERL-Net: Entangled Representation Learning for Single Image De-Raining
Code, Image Retrieval
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Efficient Large-scale Image Search With a Vocabulary Tree
* Evaluating Image Retrieval
* Learning With Average Precision: Training Image Retrieval With a Listwise Loss
Code, Image Retrieval, C++
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Efficient Large-scale Image Search With a Vocabulary Tree
Code, Image Search
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Spatial-Content Image Search in Complex Scenes
Code, Image Stitching
* *Panorama Tools
* *XuvTools: eXtend yoUr View Toolkit
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Code, Image Synthesis
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* High-fidelity Synthesis with Disentangled Representation
* Image Synthesis From Reconfigurable Layout and Style
* OASIS: Only Adversarial Supervision for Semantic Image Synthesis
Code, Impulse Noise
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* PARIGI: a Patch-based Approach to Remove Impulse-Gaussian Noise from Images
Code, Indoor Model
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
* Floor-SP: Inverse CAD for Floorplans by Sequential Room-Wise Shortest Path
Code, Inpainting
* *restoreInpaint
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
* Algorithm for Gaussian Texture Inpainting, An
* Coherent Semantic Attention for Image Inpainting
* Combined First and Second Order Total Variation Inpainting using Split Bregman
* Free-Form Image Inpainting With Gated Convolution
* Image Inpainting With Learnable Bidirectional Attention Maps
* Progressive Reconstruction of Visual Structure for Image Inpainting
* Recurrent Temporal Aggregation Framework for Deep Video Inpainting
* Total Variation Inpainting Using Split Bregman
* Variational Framework for Non-Local Inpainting
* Vision-Infused Deep Audio Inpainting
13 for Code, Inpainting
Code, InSAR
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor
Code, Interactive Segmentation
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Specifying Object Attributes and Relations in Interactive Scene Generation
Code, Interest Pointe
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* USIP: Unsupervised Stable Interest Point Detection From 3D Point Clouds
Code, Interest Points
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Matching Features without Descriptors: Implicitly Matched Interest Points
* SIPs: Succinct Interest Points from Unsupervised Inlierness Probability Learning
Code, Interpolation
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Reversibility Error of Image Interpolation Methods: Definition and Improvements
Code, Iris Recognition
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Iris Biometrics: From Segmentation to Template Security
* OSIRIS: An open source iris recognition software
Code, Isocontour
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Probability Density Estimation Using Isocontours and Isosurfaces: Applications to Information-Theoretic Image Registration
Code, JPEG Analysis
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* ZERO: a Local JPEG Grid Origin Detector Based on the Number of DCT Zeros and its Applications in Image Forensics
Code, JPEG
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Reliable JPEG Quantization Table Estimator, A
Code, Kalman Filter
* *Kalman Filter Library
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Introduction to the Kalman Filter, An
Code, Kernel Expansion
* *McKernel: A Library for Approximate Kernel Expansions in Log-linear Time
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Code, Landmarks
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Precision Landmark Location for Machine Vision and Photogrammetry: Finding and Achieving the Maximum Possible Accuracy
* Unsupervised Learning of Landmarks by Descriptor Vector Exchange
Code, Lane Detection
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
* Unsupervised Labeled Lane Markers Using Maps
Code, Layout Extimation
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
* Single-shot cuboids: Geodesics-based end-to-end Manhattan aligned layout estimation from spherical panoramas
Code, Learning
* *Torch: Machine-Learning Library
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Bidirectional One-Shot Unsupervised Domain Mapping
* Boosting Few-Shot Visual Learning With Self-Supervision
* Creativity Inspired Zero-Shot Learning
* Cross-X Learning for Fine-Grained Visual Categorization
* Deep Metric Transfer for Label Propagation with Limited Annotated Data
* Delving into Inter-Image Invariance for Unsupervised Visual Representations
* Meta R-CNN: Towards General Solver for Instance-Level Low-Shot Learning
* OSCAR: Object-Semantics Aligned Pre-Training for Vision-Language Tasks
* S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration
* Scaling and Benchmarking Self-Supervised Visual Representation Learning
* Semi-Supervised Learning by Augmented Distribution Alignment
* Symmetry and Group in Attribute-Object Compositions
* Unsupervised Pre-Training of Image Features on Non-Curated Data
18 for Code, Learning
Code, Least Squares
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Analysis of Sketched IRLS for Accelerated Sparse Residual Regression, An
Code, Lens Distortion
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Algebraic Lens Distortion Model Estimation
* Iterative Optimization Algorithm for Lens Distortion Correction Using Two-Parameter Models, An
Code, Level Set Segmentation
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Level Set Curve Evolution Partitioning of Polarimetric Images
* Variational and Level Set Methods in Image Segmentation
Code, Levenberg-Marquardt
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Algorithm for Least-Squares Estimation of Nonlinear Parameters, An
* Levenberg-Marquardt nonlinear least squares algorithms in C/C++
Code, LIDAR Processing
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* waveformlidar: An R Package for Waveform LiDAR Processing and Analysis
Code, LIDAR
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Gated2Depth: Real-Time Dense Lidar From Gated Images
Code, Lifetime
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
* Survival Forest for Left-Truncated Right-Censored Data
Code, Line Detection
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Iterative Hough Transform for Line Detection in 3D Point Clouds
Code, Line Segments
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Gestaltic Grouping of Line Segments
* LSD: a Line Segment Detector
Code, Localization
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* IM2GPS: estimating geographic information from a single image
* Prior Guided Dropout for Robust Visual Localization in Dynamic Environments
* Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization
Code, Mammography
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Efficient presentation of DICOM mammography images using Matlab
Code, Matching
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Exploring Patch Similarity in an Image
* Feature Correspondence Via Graph Matching: Models and Global Optimization
* Implementation of the Self-Similarity Descriptor
* LIBPMK: A Pyramid Match Toolkit
* Local Region Expansion: A Method for Analyzing and Refining Image Matches
* Matching of Weakly-Localized Features under Different Geometric Models
* Modal Matching for Correspondence and Recognition
* Probabilistic Model Distillation for Semantic Correspondence
* Semantic Part Detection via Matching: Learning to Generalize to Novel Viewpoints From Limited Training Data
* Software Library for Appearance Matching (SLAM)
13 for Code, Matching
Code, Mathematical Software
* *NIST Guide to Available Mathematical Software
Code, Matlab
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Robust Jointly Sparse Regression with Generalized Orthogonal Learning for Image Feature Selection
Code, Matting
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Indices Matter: Learning to Index for Deep Image Matting
Code, Mean Shift
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Implementation of the Mean Shift Algorithm, An
Code, Medical Analysis
* *Stain Normalization toolbox for histopathology image analysis
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Code, Medical Image Analysis
* *Insight Segmentation and Registration Toolkit (ITK)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Code, Mesh Compression
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Progressive Compression of Triangle Meshes
Code, Mesh Generation
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Implementation and Parallelization of the Scale Space Meshing Algorithm, An
Code, Mesh Models
* *VolMorph Documentation
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* ply2vri
* Zippered Polygon Meshes from Range Images
Code, Mesh Pose
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Neural Pose Transfer by Spatially Adaptive Instance Normalization
Code, Mesh
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* TexturePose: Supervising Human Mesh Estimation With Texture Consistency
Code, Metric Learning
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Collect and Select: Semantic Alignment Metric Learning for Few-Shot Learning
* MIC: Mining Interclass Characteristics for Improved Metric Learning
Code, MGLM
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Multivariate General Linear Models (MGLM) on Riemannian Manifolds with Applications to Statistical Analysis of Diffusion Weighted Images
Code, Model Compression
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Learning Accurate Performance Predictors for Ultrafast Automated Model Compression
Code, Modes
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Mode-Finding for Mixtures of Gaussian Distributions
Code, Moments
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Moment Matching for Multi-Source Domain Adaptation
Code, Monocular Depth
* *Recurrent Asynchronous Multimodal Networks + Events, Frames, Semantic labels, and Depth maps recorded in CARLA simulator
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Code, Morphology
* *Mathematical Morphology
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Adaptive Anisotropic Morphological Filtering Based on Co-Circularity of Local Orientations
Code, Mosaic
* *Photosynth
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Scene Collages and Flexible Camera Arrays
Code, Motion Blur
* 3-D Shape Estimation and Image Restoration: Exploiting Defocus and Motion-Blur
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* E-CIR: Event-Enhanced Continuous Intensity Recovery
Code, Motion Capture
* *CMU Graphics Lab Motion Capture Database
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Code, Motion Segmentation
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Implementation of Bilayer Segmentation of Live Video
* Motion Segmentation in the Presence of Outlying, Incomplete, or Corrupted Trajectories
Code, Motion
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Compositional Video Prediction
* Learning to Estimate Hidden Motions with Global Motion Aggregation
* Linear Algorithm for Motion from Three Weak Perspective Images Using Euler Angles
Code, MR Reconstruction
* *Synergistic Image Reconstruction Framework SIRF
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Code, Mumford-Shah
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* PALMS Image Partitioning: A New Parallel Algorithm for the Piecewise Affine-Linear Mumford-Shah Model
Code, Music Processing
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Staff Line Removal Toolkit for Gamera
Code, Network Pruning
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Resolution Switchable Networks for Runtime Efficient Image Recognition
Code, Neural Netowrks
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking
* PR Product: A Substitute for Inner Product in Neural Networks
Code, Neural Nets
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* WeightNet: Revisiting the Design Space of Weight Networks
Code, Neural Networks
* *Deep Learning Tool Kit for Medical Imaging
* *McKernel: A Library for Approximate Kernel Expansions in Log-linear Time
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Bit-Flip Attack: Crushing Neural Network With Progressive Bit Search
* Decision explanation and feature importance for invertible networks
* Enhanced neural gas network for prototype-based clustering
* GhostNets on Heterogeneous Devices via Cheap Operations
* gvnn: Neural Network Library for Geometric Computer Vision
* MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning
* Multinomial Distribution Learning for Effective Neural Architecture Search
* Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild
* Pattern Recognition with Neural Networks in C++
* Universally Slimmable Networks and Improved Training Techniques
13 for Code, Neural Networks
Code, Noise Estimation
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Analysis and Extension of the Ponomarenko et al. Method, Estimating a Noise Curve from a Single Image
Code, Noise Removal
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Analysis and Implementation of the FFDNet Image Denoising Method, An
* EPLL: An Image Denoising Method Using a Gaussian Mixture Model Learned on a Large Set of Patches
Code, Normalization
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity
Code, Numerical Algorithms
Section: Books, Collections, Overviews, General, and Surveys (H)
* Numerical Recipes in C: The Art of Scientific Computing
Code, Object Detection
* 100 lines of code for shape-based object localization
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* CenterNet: Keypoint Triplets for Object Detection
* Delving Into Robust Object Detection From Unmanned Aerial Vehicles: A Deep Nuisance Disentanglement Approach
* Development of Fast Refinement Detectors on AI Edge Platforms
* Double Head Predictor based Few-Shot Object Detection for Aerial Imagery
* Dynamic Head: Unifying Object Detection Heads with Attentions
* EGNet: Edge Guidance Network for Salient Object Detection
* Enriched Feature Guided Refinement Network for Object Detection
* Explore Spatio-Temporal Aggregation for Insubstantial Object Detection: Benchmark Dataset and Baseline
* FCOS: Fully Convolutional One-Stage Object Detection
* Integral Object Mining via Online Attention Accumulation
* Investigating Attention Mechanism in 3D Point Cloud Object Detection
* Learning Rich Features at High-Speed for Single-Shot Object Detection
* Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud
* Multiview Detection with Feature Perspective Transformation
* OTA: Optimal Transport Assignment for Object Detection
* Progressive End-to-End Object Detection in Crowded Scenes
* RepPoints: Point Set Representation for Object Detection
* Scale-Aware Trident Networks for Object Detection
* SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects
* Single-Domain Generalized Object Detection in Urban Scene via Cyclic-Disentangled Self-Distillation
* Stacked Cross Refinement Network for Edge-Aware Salient Object Detection
* TKD: Temporal Knowledge Distillation for Active Perception
* Towards Interpretable Object Detection by Unfolding Latent Structures
* UAVision: A Modular Time-Constrained Vision Library for Color-Coded Object Detection
32 for Code, Object Detection
Code, Object Recognition
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Spatial Priors for Part-Based Recognition Using Statistical Models
* Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition
Code, OCR
* *GOCR
* *Google Tesseract-OCR
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Nist Form-Based Handprint Recognition System (Release 2.2)
Code, Odometry
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Optical Flow Field Computations and Use (H)
* Data-Efficient Collaborative Decentralized Thermal-Inertial Odometry
* Event-aided Direct Sparse Odometry
* VIMO: Simultaneous Visual Inertial Model-based Odometry and Force Estimation
Code, Omnidirectional Images
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Toolbox and dataset for the development of saliency and scanpath models for omnidirectional/360° still images
Code, Open Source
* *AAM Building
* *C++ Template Image Processing Library
* *LTI-Lib
* *Mimas
* *OpenCV
* *OpenVidia
* *OSGeo: Open Source Geospatial Foundation
* *VXL
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
11 for Code, Open Source
Code, Optic Flow
* *Gain-Adaptive KLT Tracking and TV-L1 optical flow on the GPU
* *Optic Flow Evaluation
Section: Optical Flow Field Computations and Use (H)
* Performance of Optical Flow Techniques
* Real-Time Quantized Optical Flow
* Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow-Fields, The
Code, Optical Flow
Section: Optical Flow Field Computations and Use (H)
* Analysis and Speedup of the FALDOI Method for Optical Flow Estimation, An
* Comparison of Optical Flow Methods under Stereomatching with Short Baselines
* E-RAFT: Dense Optical Flow from Event Cameras
* Horn-Schunck Optical Flow with a Multi-Scale Strategy
* Implementation of Combined Local-Global Optical Flow, An
* Inverse Compositional Algorithm for Parametric Registration, The
* Joint TV-L1 Optical Flow and Occlusion Estimation
* Line Search Multilevel Truncated Newton Algorithm for Computing the Optical Flow, A
* On Anisotropic Optical Flow Inpainting Algorithms
* Robust Discontinuity Preserving Optical Flow Methods
* Robust Optical Flow Estimation
* TV-L1 Optical Flow Estimation
13 for Code, Optical Flow
Code, Optimization
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Librjmcmc: An Open-source Generic C++ Library For Stochastic Optimization
* Sparse Non-linear Least Squares Optimization for Geometric Vision
Code, Optimization, C++
* *Ceres Solver
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Code, Otsu Segmentation
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* C++ Implementation of Otsu's Image Segmentation Method, A
Code, Pansharpening
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Implementation of Nonlocal Pansharpening Image Fusion
Code, Pattern Recognition
* *MultiSpec: A Freeware Multispectral Image Data Analysis System
* *Presto-Box: Pattern REcognition Scilab TOolBOX
* *PRTools: The Matlab Toolbox for Pattern Recognition
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Code, PCA
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Framework for Robust Subspace Learning, A
Code, Pedestrian Detection
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Mask-Guided Attention Network for Occluded Pedestrian Detection
Code, Perceptual Grouping
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Computing Perceptual Organization in Computer Vision
* in-depth study of graph partitioning measures for perceptual organization, An
Code, PET Reconstruction
* *Synergistic Image Reconstruction Framework SIRF
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Code, Phase Retrieval
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Robust Phase Retrieval with the Swept Approximate Message Passing (prSAMP) Algorithm
Code, Phase Unwrapping
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Phase Unwrapping using a Joint CNN and SQD-LSTM Network
Code, Plant Phenotype
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* EasyIDP: A Python Package for Intermediate Data Processing in UAV-Based Plant Phenotyping
Code, Point Alignment
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Contrario 3D Point Alignment Detection Algorithm, A
Code, Point Cloud Convolutions
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds
Code, Point Cloud Registration
* *TEASER++: Certifiable 3D Registration
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Code, Point Cloud
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Progressive Point Cloud Deconvolution Generation Network
* Quantitative Comparison of Point Cloud Compression Algorithms With PCC Arena
Code, Point Spread Function
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Recovering the Subpixel PSF from Two Photographs at Different Distances
Code, Poisson Solver
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Analysis and Implementation of Multigrid Poisson Solvers With Verified Linear Complexity, An
Code, Poisson
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Poisson Image Editing
Code, Pose Calibration
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Orthographic Projection Model for Pose Calibration of Long Focal Images, The
Code, Pose Estimation
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* CullNet: Calibrated and Pose Aware Confidence Scores for Object Pose Estimation
* Motion Guided 3d Pose Estimation from Videos
* On Evaluation of 6D Object Pose Estimation
* Unsupervised Shape and Pose Disentanglement for 3d Meshes
Code, Pose
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* MarkerPose: Robust Real-time Planar Target Tracking for Accurate Stereo Pose Estimation
Code, Posture
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Local Assessment of Statokinesigram Dynamics in Time: An in-Depth Look at the Scoring Algorithm
Code, Pretraining
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* How Useful Is Self-Supervised Pretraining for Visual Tasks?
Code, PSF Estimation
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Non-parametric sub-pixel local point spread function estimation
Code, Python
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Analysis and Implementation of the HDR+ Burst Denoising Method, An
Code, Query
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Improving One-Stage Visual Grounding by Recursive Sub-query Construction
Code, Radar
* *Radar Tools
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Code, Radiometric Calibration
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Radiometric Self Calibration
Code, Random Forest
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Confidence intervals for the random forest generalization error
Code, Range Registration
* *VripPack: Volumetric Range Image Processing Package
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Code, RANSAC
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Automatic RANSAC by Likelihood Maximization
Code, Raw Data
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Image Unprocessing: A Pipeline to Recover Raw Data from sRGB Images
Code, RBF
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* RBF-Softmax: Learning Deep Representative Prototypes with Radial Basis Function Softmax
Code, Re-Identification
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification
* Dual-Path Model With Adaptive Attention for Vehicle Re-Identification, A
* Mixed High-Order Attention Network for Person Re-Identification
* MVP Matching: A Maximum-Value Perfect Matching for Mining Hard Samples, With Application to Person Re-Identification
* Omni-Scale Feature Learning for Person Re-Identification
* Robust Person Re-Identification by Modelling Feature Uncertainty
* Robust Re-identification by Multiple Views Knowledge Distillation
* Self-Similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-Identification
* Spectral Feature Transformation for Person Re-Identification
11 for Code, Re-Identification
Code, Recognition
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Attention Pyramid Module for Scene Recognition
* Hybrid Approach to Tiger Re-Identification, A
* Part-Pose Guided Amur Tiger Re-Identification
* Pose-Guided Complementary Features Learning for Amur Tiger Re-Identification
* Strong Baseline for Tiger Re-ID and its Bag of Tricks, A
7 for Code, Recognition
Code, Rectification
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Quasi-Euclidean Epipolar Rectification
* Rectification for any epipolar geometry
Code, Recurrent Networks
* *Recurrent Asynchronous Multimodal Networks + Events, Frames, Semantic labels, and Depth maps recorded in CARLA simulator
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Code, Region Matching
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Affine Invariant Patch Similarity, An
Code, Registration
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* AROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data
* elastix: A Toolbox for Intensity-Based Medical Image Registration
* Few-Shot Unsupervised Image-to-Image Translation
* Improvements of the Inverse Compositional Algorithm for Parametric Motion Estimation
* Iterative Image Registration Technique with an Application to Stereo Vision, An
8 for Code, Registration
Code, Regularization
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Delving Deep Into Label Smoothing
* Isotonic Modeling with Non-Differentiable Loss Functions with Application to Lasso Regularization
Code, Relations
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Heterogeneous Representation Learning and Matching for Few-Shot Relation Prediction
* Visual Relation Grounding in Videos
Code, Relighting
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Deep Single-Image Portrait Relighting
* Lighting Sensitive Display
Code, Rendering
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Accelerating Monte Carlo Renderers by Ray Histogram Fusion
* Soft Rasterizer: A Differentiable Renderer for Image-Based 3D Reasoning
Code, Representation Learning
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* On the Integration of Self-Attention and Convolution
Code, Restoration
* *restoreInpaint
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Code, Retinex
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Center/Surround Retinex: Analysis and Implementation
* Multiscale Retinex
* Retinex in Matlab
* Retinex Poisson Equation: a Model for Color Perception
* Screened Poisson Equation for Image Contrast Enhancement
Code, Retinex, Matlab
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Retinex in Matlab
Code, Retrieval
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Adaptive Offline Quintuplet Loss for Image-text Matching
Code, RGB-D
* *Hydra:
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Code, Robust Fitting
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Deterministic Approximate Methods for Maximum Consensus Robust Fitting
Code, Saliency
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Deep Learning for Light Field Saliency Detection
* Generation and Detection of Alignments in Gabor Patterns
* PointCloud Saliency Maps
* SaltiNet: Scan-Path Prediction on 360 Degree Images Using Saliency Volumes
7 for Code, Saliency
Code, SAR Filters
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Non-Local Means Filters for Full Polarimetric Synthetic Aperture Radar Images with Stochastic Distances
Code, SAR
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms
Code, SAR, Matlab
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms
Code, Scale Space
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Finite Difference Schemes for MCM and AMSS
Code, Scene Flow
Section: Optical Flow Field Computations and Use (H)
* Learning Scene Dynamics from Point Cloud Sequences
Code, Scene Graph
* *Hydra:
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Code, Search
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Consensus Maximization Tree Search Revisited
* Progressive Differentiable Architecture Search: Bridging the Depth Gap Between Search and Evaluation
Code, Segmenation Evaluation
Section: Books, Collections, Overviews, General, and Surveys (H)
* Automated Performance Evaluation of Range Image Segmentation
Code, Segmentation
* *Edison: Edge Detection and Image SegmentatiON system
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* AdaptIS: Adaptive Instance Selection Network
* Adaptive Early-Learning Correction for Segmentation from Noisy Annotations
* AMP: Adaptive Masked Proxies for Few-Shot Segmentation
* Asymmetric Non-Local Neural Networks for Semantic Segmentation
* Automatic 1D Histogram Segmentation and Application to the Computation of Color Palettes
* Bayesian Adaptive Superpixel Segmentation
* Berkeley Segmentation Dataset and Benchmark, The
* C++ Implementation of Otsu's Image Segmentation Method, A
* CCNet: Criss-Cross Attention for Semantic Segmentation
* Code: Active Segmentation With Fixation
* Confidence Regularized Self-Training
* Consistency-Regularized Region-Growing Network for Semantic Segmentation of Urban Scenes With Point-Level Annotations
* Contrastive and Selective Hidden Embeddings for Medical Image Segmentation
* Crossover-Net: Leveraging vertical-horizontal crossover relation for robust medical image segmentation
* Disentangled Non-local Neural Networks
* Dynamic Threshold Determination by Local and Global Edge Evaluation
* Efficient Graph-Based Image Segmentation
* Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision, An
* Graph Partitioning Active Contours (GPAC) for Image Segmentation
* InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting
* Intellegent Scissors: Interactive tool for image segmentation
* Interactive Segmentation Based on Component-trees
* Layered Embeddings for Amodal Instance Segmentation
* Level-set image segmenation software
* Matlab toolbox for Level Set Methods
* Normalized cut image segmenation software
* Ratio Contour Code
* Robust Analysis of Feature Spaces: Color Image Segmentation
* Segmentation skin cancer images
* Segmentation with Active Contours
* Semantic-Oriented Labeled-to-Unlabeled Distribution Translation for Image Segmentation
* ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors
* ShelfNet for Fast Semantic Segmentation
* SOLO: Segmenting Objects by Locations
* Strip Pooling: Rethinking Spatial Pooling for Scene Parsing
* Watervoxels
41 for Code, Segmentation
Code, Segmentation, C
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Normalized cut image segmenation software
Code, Segmentation, C++
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* C++ Implementation of Otsu's Image Segmentation Method, A
* Robust Analysis of Feature Spaces: Color Image Segmentation
Code, Segmentation, Matlab
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Matlab toolbox for Level Set Methods
Code, Semantic Segmentation
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Event-based Asynchronous Sparse Convolutional Networks
* Semantic Segmentation: A Zoology of Deep Architectures
* Study of RobustNet, a Domain Generalization Method for Semantic Segmentation, A
Code, Shape from Shading
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Integration of Shape from Shading and Stereo
* Shape From Shading Using Linear-Approximation
* Shape from Shading: A Survey
Code, SIFT
* *SIFT Feature Detector
* *VLFeat
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* ASIFT: An Algorithm for Fully Affine Invariant Comparison
* Distinctive Image Features from Scale-Invariant Keypoints
Code, Signal Processing
* *IT++ Mathematical, Signal Processing and Communication Routines
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Signal Processing Algorithms in Fortran and C
* Signal Processing Algorithms in MATLAB
Code, Signal Processing, C++
* *IT++ Mathematical, Signal Processing and Communication Routines
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Code, Skeleton
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Finding the Skeleton of 2D Shape and Contours: Implementation of Hamilton-Jacobi Skeleton
Code, Skin Spots
* *APP for Monitoring Skin Spots
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Code, SLAM
* *Kimera
* *Ultimate SLAM
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Continuous-Time vs. Discrete-Time Vision-based SLAM: A Comparative Study
* SLAMANTIC: Leveraging Semantics to Improve VSLAM in Dynamic Environments
* tinySLAM: A SLAM algorithm in less than 200 lines C-language program
Code, SLIC
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Bilateral K-Means for Superpixel Computation (the SLIC Method)
Code, Snakes
* *Mega Wave
* *qsnake_demo
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Code: Active Segmentation With Fixation
* Gradient Vector Flow: A New External Force for Snakes
* Real Time Morphological Snakes Algorithm, A
7 for Code, Snakes
Code, Space Envelope
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Space Envelope: A Representation for 3D Scenes, The
Code, Spectal Bias
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* On Measuring and Controlling the Spectral Bias of the Deep Image Prior
Code, Spectral Clustering
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* CAEclust: A Consensus of Autoencoders Representations for Clustering
Code, Splines
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Theory and Practice of Image B-Spline Interpolation
Code, Stabilization
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Mao-Gilles Stabilization Algorithm
Code, Steerable Filter
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Steerable Pyramid: A Flexible Architecture for Multi-Scale Derivative Computation, The
Code, Stereo Matching
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Bilaterally Weighted Patches for Disparity Map Computation
* Deep Material-Aware Cross-Spectral Stereo Matching
* Fast Cost-Volume Filtering for Visual Correspondence and Beyond
* Kolmogorov and Zabih's Graph Cuts Stereo Matching Algorithm
* Stereo Disparity through Cost Aggregation with Guided Filter
Code, Stereo
* *MSRC Stereo Vision C# SDK, The
* *Real Time Dense Stereo
* *SRI Stereo Engine
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* ChiTransformer: Towards Reliable Stereo from Cues
* Computing Visual Correspondence with Occlusions via Graph Cuts
* Disparity Estimation Networks for Aerial and High-Resolution Satellite Images: A Review
* Efficient Belief Propagation for Early Vision
* On the Over-Smoothing Problem of CNN Based Disparity Estimation
* Point-Based Multi-View Stereo Network
* Polar Epipolar Rectification, The
* Shape and the Stereo Correspondence Problem
* Stereo Matching With Nonlinear Diffusion
* Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms, A
15 for Code, Stereo
Code, STIP
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Evaluation of local spatio-temporal features for action recognition
Code, Structure from Motion
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Automatic Non-rigid 3D Modeling from Video
* Bundler: Structure from Motion for Unordered Image Collections
Code, Structured Light
* *Kinect-Like 3D camera
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Code, Style Transfer
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Photorealistic Style Transfer via Wavelet Transforms
Code, Super-Resolution
* *Super-Resolution Code
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Super-Resolution Imaging
Code, Super Resolution
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Implementing Handheld Burst Super-Resolution
* Lightweight and Accurate Recursive Fractal Network for Image Super-Resolution
* Robust Temporal Super-Resolution for Dynamic Motion Videos
* Single image super-resolution from transformed self-exemplars
Code, Superpixel
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Bilateral K-Means for Superpixel Computation (the SLIC Method)
Code, Superresolution
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Constrained and Unconstrained Inverse Potts Modelling for Joint Image Super-Resolution and Segmentation
Code, Support Vector Machines
* *LIBSVMTL: a Support Vector Machine Template Library
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* LIBSVM: a library for support vector machines
Code, SURF
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Analysis of the SURF Method, An
Code, Surface Appearance
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Time-varying Surface Appearance: Acquisition, Modeling, and Rendering
Code, Surface Fitting
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Linear Fitting with Missing Data for Structure-from-Motion
Code, Surfaces, Matlab
Section: Books, Collections, Overviews, General, and Surveys (H)
* Modeling of Curves and Surfaces with MATLAB®
Code, Surgery
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* IGSTK: an open source software toolkit for image-guided surgery
Code, SVD
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* SVD: A Large-Scale Short Video Dataset for Near-Duplicate Video Retrieval
Code, Swin Transform
* *Swin-Transformer-Object-Detection
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Code, Symmetry
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Gradient Product Transform: An Image Filter for Symmetry Detection, The
* Learning to Reconstruct Symmetric Shapes using Planar Parameterization of 3D Surface
Code, Target Detection
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
* Portability Study of an OpenCL Algorithm for Automatic Target Detection in Hyperspectral Images
Code, Tensor Algebra
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Spherical Tensor Algebra: A Toolkit for 3D Image Processing
Code, Terrain
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Modeling Extent-of-Texture Information for Ground Terrain Recognition
Code, Text Detection
Section: OCR, Document Analysis and Character Recognition Systems (H)
* State-of-the-Art in Action: Unconstrained Text Detection
Code, Texture Analysis
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* JAVA-based Texture Analysis Employing Neighborhood Gray-Tone Difference Matrix (NGTDM) for Optimization of Land Use Classifications in High Resolution Remote Sensing Data
Code, Texture Analysis, Java
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* JAVA-based Texture Analysis Employing Neighborhood Gray-Tone Difference Matrix (NGTDM) for Optimization of Land Use Classifications in High Resolution Remote Sensing Data
Code, Texture Synthesis
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Efros and Freeman Image Quilting Algorithm for Texture Synthesis
* Micro-Texture Synthesis by Phase Randomization
Code, Texture
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Cartoon+Texture Image Decomposition
Code, TIFF
* *LibTIFF: TIFF Library and Utilities
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Code, Time Series
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
* Association Rules Discovery of Deviant Events in Multivariate Time Series: An Analysis and Implementation of the SAX-ARM Algorithm
Code, Time Warping
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Generalized Canonical Time Warping
Code, Total Variation
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Chambolle's Projection Algorithm for Total Variation Denoising
* Rudin-Osher-Fatemi Total Variation Denoising using Split Bregman
* Total Variation Deconvolution Using Split Bregman
Code, Tracking
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* DeepTAM: Deep Tracking and Mapping with Convolutional Neural Networks
* Design and Implementation of People Tracking Algorithms for Visual Surveillance Applications
* Fast Visual Object Tracking using Ellipse Fitting for Rotated Bounding Boxes
* Fragments Tracker
* GPU_KLT: A GPU-based Implementation of the Kanade-Lucas-Tomasi Feature Tracker
* KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker
* Learning Discriminative Model Prediction for Tracking
* Learning the Statistics of People in Images and Video
* Lucas-Kanade 20 Years On
* MITT: Medical Image Tracking Toolbox
* Robust Multi-Modality Multi-Object Tracking
* Skimming-Perusal Tracking: A Framework for Real-Time and Robust Long-Term Tracking
* STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos
* Tracker Fusion for Robustness in Visual Feature Tracking
* Tracking by an Optimal Sequence of Linear Predictors
* Tracking Vector Magnetograms with the Magnetic Induction Equation
22 for Code, Tracking
Code, Training
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Activate or Not: Learning Customized Activation
* t-vMF Similarity For Regularizing Intra-Class Feature Distribution
Code, Tranformations
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Highly-Expressive Spaces of Well-Behaved Transformations: Keeping it Simple
Code, Tree Bark
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* CNN-based Method for Segmenting Tree Bark Surface Singularites
Code, Turbulence
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Implementation of the Centroid Method for the Correction of Turbulence
* Study of the Principal Component Analysis Method for the Correction of Images Degraded by Turbulence
Code, UAV
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applications
Code, Vanishing Points
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Unsupervised Point Alignment Detection Algorithm, An
* Vanishing Point Detection in Urban Scenes Using Point Alignments
Code, Vascular tree
* *Vascular Modeling Toolkit, The
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* OpenCCO: An Implementation of Constrained Constructive Optimization for Generating 2D and 3D Vascular Trees
Code, Vectorization
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Binary Shape Vectorization by Affine Scale-space
Code, Vehicle Detection
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Connecting Language and Vision for Natural Language-Based Vehicle Retrieval
Code, Vehicle Synthesis
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Simulating Content Consistent Vehicle Datasets with Attribute Descent
Code, Video Analysis
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* AWSD: Adaptive Weighted Spatiotemporal Distillation for Video Representation
Code, Video Deblurring
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Implementation of Local Fourier Burst Accumulation for Video Deblurring
Code, Video Denoising
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Video Denoising with Optical Flow Estimation
Code, Video Interpolation
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* PoSNet: 4x Video Frame Interpolation Using Position-Specific Flow
Code, Video Noise
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Signal-dependent Video Noise Estimator Via Inter-frame Signal Suppression, A
Code, Video Object Segmentatioin
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* RANet: Ranking Attention Network for Fast Video Object Segmentation
Code, Video Processing
* *Rad Video Tools
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Efficient 3D Video Engine Using Frame Redundancy
* Practical Image and Video Processing Using MATLAB
* SlowFast Networks for Video Recognition
7 for Code, Video Processing
Code, Video Processing, Matlab
Section: Books, Collections, Overviews, General, and Surveys (H)
* Practical Image and Video Processing Using MATLAB
Code, Video Recognition
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Video Transformer Network
Code, Video Segmentation
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing
Code, Video Understanding
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Graph-Based Framework to Bridge Movies and Synopses, A
* TSM: Temporal Shift Module for Efficient Video Understanding
Code, Viedo Denoise
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Implementation of VBM3D and Some Variants
Code, View Synthesis
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Pose-Based View Synthesis for Vehicles: A Perspective Aware Method
Code, Viewing
* *Lotus Hill Institute
Code, Virtual Reality
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* UnrealCV: Connecting Computer Vision to Unreal Engine
Code, Vision Transformer
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* CvT: Introducing Convolutions to Vision Transformers
Code, Visual Effects
Section: Books, Collections, Overviews, General, and Surveys (H)
* Computer Vision for Visual Effects
Code, Visual Learning
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Visual Understanding via Multi-Feature Shared Learning With Global Consistency
Code, Visual Odometry
* *SVO Pro: Semi-direct Visual-Inertial Odometry and SLAM for Monocular, Stereo, and Wide Angle Cameras
Section: Optical Flow Field Computations and Use (H)
Code, Visual Q-A
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Why Does a Visual Question Have Different Answers?
Code, Visual Worlds
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-Supervised Learning
Code, Visualization
* *Mathematical Morphology
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Language Features Matter: Effective Language Representations for Vision-Language Tasks
* Language-Agnostic Visual-Semantic Embeddings
Code, Watermark
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Intelligent Watermarking Techniques
Code, Watershed
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Parallel, O(n) Algorithm for an Unbiased, Thin Watershed, A
Code, Wavelets
* *Mega Wave
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Wavelab
Code, Wavelets, Matlab
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Wavelab
Code, Wind Turbine
Section: Optical Flow Field Computations and Use (H)
* Single Date Wind Turbine Detection on Sentinel-2 Optical Images
Code, Wireframe
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* End-to-End Wireframe Parsing
Code, X-Ray Analysis
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Cradle Removal in X-Ray Images of Panel Paintings
Coded Aperture
Section: Coded Aperture Compressive Sensing (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Coding
Section: Coding -- Coding Theory, Communications, etc. (H2)
Section: Coding, Compression, Acoustic Signals, Sounds, Audio (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: Reconstruction from Coded Images, Error Recovery (H3)
Coffee
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Coffee Trees, Trees as Crops, Tea Trees (H4)
Cognitive Radio
Section: Cognitive Radio (H3)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Coins
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Metal, Coins (H4)
Colinear Lines
Section: Colinear Line Segments (Collinear) (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Finding Picture Edges Through Collinearity of Feature Points
Collections, Early
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Early Collections of Articles (H2)
Collections, General
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Collections -- General Computer Vision (H2)
Collections, Special Topics
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Collections, Special Topics or Conferences (H2)
Collision Avoidance
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Collision Avoidance, Collision Detection, Marine Vessels, Ships (H4)
Section: Collision Avoidance, Collision Detection, Vehicles, Objects on the Road (H4)
Section: Obstacles, Objects on the Road Using Radar, Sonar, LiDAR, Active Vision (H4)
Collision Detection
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Airplane Obstacles, Collision Detection, Sense and Avoid (H3)
Section: Collision Avoidance, Collision Detection, Marine Vessels, Ships (H4)
Section: Collision Avoidance, Collision Detection, Vehicles, Objects on the Road (H4)
Section: Focus of Expansion and Other Features (H2)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Obstacle Detection, Time to Collision Techniques (H2)
Section: Obstacles, Objects on the Road Using Radar, Sonar, LiDAR, Active Vision (H4)
Section: Optical Flow Field Computations and Use (H)
Section: Railroads, Inspection, Obstacles (H3)
Section: Target Tracking, Collision Detection (H3)
Section: Translation Only (H2)
12 for Collision Detection
Collisions
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Traffic Collisions, Accidents, Analysis, Congestion, Not Image Analysis (H4)
Colonoscopy
Section: Medical Applications -- Colonoscopy, Colon Cancer (H2)
Section: Medical Applications -- Colonoscopy, Polyp Detection, Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Color Calibration
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Color Calibration for Display and Printing (H3)
Section: Photometric Calibration, Radiometric Calibration, Spectral Calibration, Color Calibration (H2)
Color Clustering
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Defect Detection in Random Color Textures
Color Constancy
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Color Constancy, Recognition, Healey Papers (H3)
Section: Color Constancy, Recognition, Simon Fraser Univ. (Funt and Finlayson) Papers (H3)
Section: Color Constancy, Retinex (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Reflectance Computations, Albedo (H2)
* Illumination-Invariant Matching of Deterministic Local Structure in Color Images, The
7 for Color Constancy
Color Cooccurrence Matrix
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Color Texture Segmentation for Clothing in a Computer-Aided Fashion Design System
Color Correction
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Color Correction (H3)
Section: Color Transfer, Color Enhancement, Color Correction (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Haze, Dehazing, Color Correction (H3)
Section: Lighting Effects, View Generation, Graphics Issues (H3)
Section: Underwater Imaging, Color Correction, Restoration (H3)
Section: Underwater Object Detection (H4)
8 for Color Correction
Color Histogram Matching
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Histogram Matching, Histogram Comparisons (H3)
Section: Recognition by Color Indexing (H2)
Color Image Restoration
Section: Color, Multispectral, Multi-Channel Restoration (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Color Indexing
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Recognition by Color Indexing (H2)
* Automatic Detection of Human Nudes
* Finding Waldo, or Focus of Attention Using Local Color Information
* Image Retrieval Using Fuzzy Evaluation of Color Similarity
* Query by Image and Video Content: The QBIC System
8 for Color Indexing
Color Matching
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Recognition by Color Indexing (H2)
Color Models
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Color Models, Color Representation (H2)
Section: Color Sensors, Sensor Models (H3)
Section: Color Transfer, Color Enhancement, Color Correction (H3)
Section: Computational Models of Color, Computer Based Color Models (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Reflections and Color Models, Reflectance (H3)
* Flexible Color Point Distribution Models
* Region Competition and its Analysis: A Unified Theory for Image Segmentation
9 for Color Models
Color Perception, Survey
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Survey on Color: Aspects of Perception and Computation
Color Quantization
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Color Quantization of Images (H4)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Tone Mapping of Images (H4)
* Color Texture Segmentation for Clothing in a Computer-Aided Fashion Design System
Color Segmentation
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Color Applied to Segmentation (H1)
Section: Color Segmentation, Healey (H2)
Section: Complete Segmentation Systems Based on Ohlander Technique (H2)
* Color Pixels Classification in an Hybrid Color Space
* Computational Techniques in the Visual Segmentation of Static Scenes
* Detection of Defects in Colour Texture Surfaces
8 for Color Segmentation
Color Sensors
Section: Color Sensors, Sensor Models (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Color Texture
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Color Textures and Texture with Color (H2)
Color to Gray
Section: Colorization, Gray, Color-to-Gray, Color Models (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Color Transfer
Section: Color Transfer, Color Enhancement, Color Correction (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Color
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Color and Its Use in Computer Vision (H1)
Section: Color Compression, Multispectral Image Coding and Compression (H2)
Section: Color Edge Detectors (H1)
Section: Color Image Quality, Hyperspectral Image Quality (H3)
Section: Color in Image Enhancement (H2)
Section: Color Textures and Texture with Color (H2)
Section: Color, General Issues (H2)
Section: Color, Multispectral, RGB, for Salient Regions (H4)
Section: Complete Segmentation Systems Based on Ohlander Technique (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Database Indexing Using Color and Shape or Regions (H3)
Section: Database Indexing Using Color (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Face Analysis, Shading, Illumination, Lighting and Color Variations (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Finding Faces by Color Features (H3)
Section: Finding Objectionable Images, Harmful Content, Filtering Web Sites (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Skin Color Models, Skin Detection (H3)
Section: Texture and Color, Color and Texture, for Segmentation (H2)
Section: Tracking Faces, Heads Using Color Models (H3)
Section: Video Database Indexing, Color Analysis, Object Appearance (H4)
* Application of Color Information to Visual Perception
* ARGOS Image Understanding System, The
* Automatic Watershed Segmentation of Randomly Textured Color Images
* Color Image Processing for Navigation: Two Road Trackers
* Color Metric for Computer Vision, A
* Color Vision Cells Found in Visual Cortex
* Color-Encoded Structured Light for Rapid Active Ranging
* Computer Image Segmentation: Structured Merge Strategies
* Extracting Shape and Reflectance of Hybrid Surfaces by Photometric Sampling
* Face Detection and Gesture Recognition for Human-Computer Interaction
* From Image Measurements to Object Hypotheses
* Measurement Techniques for Spectral Characterization for Remote Sensing
* Picture Segmentation Using a Recursive Region Splitting Method
* Results Using Random Field Models for the Segmentation of Color Images
* Scene Segmentation by Cluster Detection in Color Space
* Semantic-Free Approach to 3-D Robot Color Vision, A
* vision system for automatic inspection of meat quality, A
46 for Color
Color, Edges
Section: Color Edge Detectors (H1)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Color, Face Recognition
Section: Face Analysis, Shading, Illumination, Lighting and Color Variations (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Color, Shape
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Shape Using Color Images, Color Photometric Stereo (H2)
Color, Transforms
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Production System for Region Analysis, A
Colorization
Section: Colorization, Gray, Color-to-Gray, Color Models (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Combination
Section: Classifier Combination, Evaluation, Overview, Appliction Specific (H4)
Section: Decision Fusion (H3)
Section: Hierarchical Combination, Multi-Stage Classifiers (H4)
Section: Multiple Classifiers Applied to Arabic Numbers (H4)
Section: Multiple Classifiers, Combining Classifiers, Combinations (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
7 for Combination
Comics
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Speech Ballons in Comics, Comic Analysis, Panel Detection (H4)
Commercial Detection
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Video Analysis, Find Ads, Find Commercials (H4)
Communication
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: Sonar for Communication, Underwater Communication (H3)
Section: Transmission Issues, MIMO, Communication (H3)
Comparisons
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Classifier, Performance Evaluation, Errors, Comparisons (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Experimental Comparison of Neural and Statistical Nonparametric Algorithms for Supervised Classification of Remote Sensing Images, An
* Experimental Comparison of Range Image Segmentation Algorithms, An
Complexity Analysis
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Faster Neighbor Finding on Images Represented By Bincodes
Complexity
Section: Computational Complexity Issues, Computation (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Compressed Images
Section: Halftone Images, Compressed Images: Image Hiding, Data Hiding, Steganography (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Reversible Data Hiding for JPEG, Steganography (H3)
Compressed Sensing
Section: Coded Aperture Compressive Sensing (H3)
Section: Compressive Sensing, Compressive Imaging, Compressed Sensing, Compression, Reconstruction (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Compression
* *Image and Video Compression
* *Still-Image Compression
* *Visual Communications and Image Processing '96
* *Visual Information Processing V
Section: Adaptive Coding Techniques (H2)
Section: Architectures and Systems for Matching for Block Coding, Block Motion Estimation (H4)
Section: Audio and Video Coding Standard, AVS Coding Issues, Standards (H3)
Section: AVC/H.264 Mode Selection, Mode Decision (H4)
Section: Block Coding, Using Block Matching (H4)
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Coding -- Coding Theory, Communications, etc. (H2)
Section: Coding, Compression, Acoustic Signals, Sounds, Audio (H3)
Section: Color Quantization of Images (H4)
Section: Computation and Matching for Block Coding, Block Motion Estimation (H4)
Section: Computation and Matching for Region Coding (H4)
Section: Computation for General Motion Compensation, Motion Estimation (H4)
Section: Computation for Motion Compensation, Block and Region Coding (H3)
Section: Computation for Vector Fields, Flow Fields (H4)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Computing Very Low Bitrate, 3-D and Object Based Coding (H4)
Section: Cosine Transform, DCT Compression (H2)
Section: Differential Pulse Code Modulation (DPCM) Coding (H2)
Section: Document Compression, Document Coding Systems and Techniques (H2)
Section: Entropy Based Vector Quantization (H3)
Section: Fractal Based Coding and Compression, Fractal Coding, Fractal Compression (H3)
Section: Full Search Block Motion Estimation, Motion Coding (H4)
Section: General Rate-Quality, Rate Distortion, Rate Control, Error Tradeoffs for Video (H3)
Section: Global Motion Compensation (H4)
Section: H.264/AVC Issues, Advanced Video Coding (H3)
Section: Hierarchical, Multi-Level, Pyramidal Coding Techniques (H2)
Section: High Efficiency Video Coding, HEVC Coding Standards (H4)
Section: High Rate Compression, Low Bit Rate Compression, Region Based Coding (H2)
Section: Huffman Coding (H2)
Section: Image Compression, Coding, Overview Section (H1)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Image Quantization, Quantization of Images (H3)
Section: Intra-Coding, Intra-Prediction Issues, AVC/H.264 (H4)
Section: JPEG 2000, Discussion, Generation, and Use, JPEG2000 (H4)
Section: JPEG Standards and Use (H3)
Section: Learning, Neural Nets for Coding, Compression in Video (H2)
Section: Matching Pursuits, Video Coding (H2)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Motion and Video Coding: General (H1)
Section: Motion and Video Coding: Hardware and Systems (H2)
Section: Motion Compensation for Coding (H4)
Section: Motion Compensation, Block, Region, Object, and Low Bit Rate Coding (H2)
Section: Moving Image Coding, Compression: Using Vector Fields, Flow Fields (H4)
Section: MPEG 4 Issues (H3)
Section: MPEG 7 Issues (H3)
Section: MPEG and Related Standard Coding Methods (H2)
Section: Multi Dimensional Coding, Stereo Coding, Disparity Maps, 3-D Shapes (H2)
Section: Neural Net Compression (H4)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Point Cloud Compression (H3)
Section: Predictive, Adaptive Vector Quantization (H3)
Section: Rate-Quality, Rate Distortion for DCT Coded Images, Wavelet Coding (H4)
Section: Rate-Quality, Rate Distortion, Rate Control, Error Tradeoffs for AVC/H.264 (H4)
Section: Scalable Video Coding, SVC, Extensions AVC/H.264 (H4)
Section: Set Partitioning in Hierarchical Trees (SPIHT) Coding (H3)
Section: Subband Coding Techniques (H3)
Section: Tone Mapping of Images (H4)
Section: Transform Coding -- General (H2)
Section: Using Arbitrary Region Coding (H4)
Section: Using Motion Compensation, Block and Region Coding (H3)
Section: Variable Size Blocks for Block Coding, Block Motion Estimation (H4)
Section: Vector Quantization Survey and General (H3)
Section: Vector Quantization with other Transform Coding Methods (H3)
Section: Vector Quantization, VQ, Applied to Motion and Video Coding (H2)
Section: Vector Quantization, VQ, Image Compression (H2)
Section: Very Low Bitrate, 3-D and Object Based Coding (H4)
Section: VVC Issues, Versatile Video Coding Standard (H3)
Section: Wavelet Coding, Compression Applications, Hardware (H4)
Section: Wavelets for Image Coding -- Zero Tree Code (H4)
Section: Wavelets for Image Coding, Compression -- Block, Region and Shape Based (H4)
Section: Wavelets for Image Coding, Compression -- Quantization Issues (H4)
Section: Wavelets for Image Compression, Image Coding (H3)
Section: Wavelets for Motion and Video Coding (H3)
* Compression of Personal Identification Pictures Using Vector Quantization with Facial Feature Correction
* Digital Pictures: Representation, Compression, and Standards
* Extreme Compression of Weather Radar Data
* Handbook of Data Compression
* illumination invariant algorithm for subpixel accuracy image stabilization and its effect on MPEG-2 video compression, An
* Image Compression Using the 2-D Wavelet Transform
* Image Data Compression: Block Truncation Coding
87 for Compression
Compression, Binary Images
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Processing and Analysis of Binary (Two Level) Images (H1)
Compression, Color
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Color Compression, Multispectral Image Coding and Compression (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Compression of Color Image via the Technique of Surface Fitting
Compression, Lossless
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Lossless Coding, Lossless Compression, Transmission (H2)
Compression, Model-Based
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Model-Based Image-Coding: Advanced Video Coding Techniques for Very-Low Bit-Rate Applications
Compression, Point Cloud
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Point Cloud Compression (H3)
Compression, Stereo
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Multi Dimensional Coding, Stereo Coding, Disparity Maps, 3-D Shapes (H2)
Compression, Video
* *Digital Video Compression: Algorithms and Technologies 1995
Section: Architectures and Systems for Matching for Block Coding, Block Motion Estimation (H4)
Section: Audio and Video Coding Standard, AVS Coding Issues, Standards (H3)
Section: AVC/H.264 Mode Selection, Mode Decision (H4)
Section: Block Coding, Using Block Matching (H4)
Section: Computation and Matching for Block Coding, Block Motion Estimation (H4)
Section: Computation and Matching for Region Coding (H4)
Section: Computation for General Motion Compensation, Motion Estimation (H4)
Section: Computation for Motion Compensation, Block and Region Coding (H3)
Section: Computing Very Low Bitrate, 3-D and Object Based Coding (H4)
Section: Distributed Video Coding (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Full Search Block Motion Estimation, Motion Coding (H4)
Section: Global Motion Compensation (H4)
Section: H.264/AVC Issues, Advanced Video Coding (H3)
Section: HDTV Issues, Coding, Transmission (H3)
Section: High Efficiency Video Coding, HEVC Coding Standards (H4)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion and Video Coding: General (H1)
Section: Motion and Video Coding: Hardware and Systems (H2)
Section: Motion Coding, Video Coding, Evaluations, Surveys (H2)
Section: Motion Compensation for Coding (H4)
Section: Motion Compensation, Block, Region, Object, and Low Bit Rate Coding (H2)
Section: Moving Image Coding, Compression: Using Vector Fields, Flow Fields (H4)
Section: MPEG 4 Issues (H3)
Section: MPEG 7 Issues (H3)
Section: MPEG and Related Standard Coding Methods (H2)
Section: Multiview Video Coding, Stereo Video Coding, 3D Video Coding (H2)
Section: Scalable Video Coding, SVC, Extensions AVC/H.264 (H4)
Section: Transmission, Television, and Television Coding (H2)
Section: Using Arbitrary Region Coding (H4)
Section: Using Motion Compensation, Block and Region Coding (H3)
Section: Variable Size Blocks for Block Coding, Block Motion Estimation (H4)
Section: Very Low Bitrate, 3-D and Object Based Coding (H4)
* Method of Coding TV Signals Based on Edge Detection, A
35 for Compression, Video
Compressive Sensing
Section: Coded Aperture Compressive Sensing (H3)
Section: Compressive Sensing, Compressive Imaging, Compressed Sensing, Compression, Reconstruction (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Convolutional Network, Deep Networks, Learning for Compressive Sensing (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Light Field Compressed Sensing (H3)
Computation
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Tensor Completion (H4)
Computational Complexity
Section: Computational Complexity Issues, Computation (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Computational Vision
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: General Computational Vision (H1)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Bayesian-approach to Binocular Stereopsis, A
* From Pixels to Predicates
* Ill-Posed Problems and Regularization Analysis in Early Vision
7 for Computational Vision
Computational Vision, Survey
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Computational Approaches to Image Understanding
* Computational Vision
* Integration of Visual Modules: An Extension of the Marr Paradigm
Computer Icons
Section: Analysis of Graphics, Symbols, Trademarks, Icons (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Concavity
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Concavity Detection (H3)
Concrete Inspection
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Pavement, Road Surface, Asphalt, Concrete (H4)
Cone-Beam Tomography
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Tomographic Image Generation, Cone-Beam, Fan-Beam, Helical, Spiral Reconstruction (H2)
Conference Reports
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Conference Listings or Special Issues, Introductions through 2004 (H1)
Section: Conference Listings or Special Issues, Introductions, 2005-2009 (H2)
Section: Conference Listings or Special Issues, Introductions, 2010-2012 (H2)
Section: Conference Listings or Special Issues, Introductions, 2013-2015 (H2)
Section: Conference Listings or Special Issues, Introductions, 2016-2018 (H2)
Section: Conference Listings or Special Issues, Introductions, 2019-2022 (H2)
Section: Conference Listings or Special Issues, Introductions, 2023- (H2)
8 for Conference Reports
Conferences
Section: Conference Names, Index of Frequent Conferences (H1)
Congestion
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Traffic Collisions, Accidents, Analysis, Congestion, Not Image Analysis (H4)
Connected Components
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Extraction and Analysis of Connected Components and Boundaries (H1)
* Sequential Operations in Digital Picture Processing
Connected Vehicles
Section: Connected Vehicles, Use, Evaluation (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Connection Machine
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Object Recognition Using the Connection Machine
* Parallel Integration of Vision Modules
* Recognition Algorithms for the Connection Machine
Connectionist
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Connectionist Approaches to Computer Vision (H1)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Connectionist Approach for Gray Level Image Segmentation, A
* Symbolic Mapping of Neurons in Feedforward Networks
Connectivity
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Extraction and Analysis of Connected Components and Boundaries (H1)
* Efficient Evaluations of Edge-Connectivity and Width Uniformity
Constraint Satisfaction
Section: Continuous Relaxation Theory, Constraint Satisfaction (H3)
Section: Discrete Relaxation Methods (H2)
Section: Discrete Relaxation Theoretical Issues (H3)
Section: Evidence Theory, Combination Techniques, Optimization Techniques (H3)
Section: Faugeras and Berthod Gradient Optimization Methods (H3)
Section: General Structure and Graph Representation, Relations, Neighbors (H2)
Section: Graph Matching Theoretical Issues (H2)
Section: Graph Matching, Continuous Relaxation, Constraint Satisfaction (H2)
Section: Graph Matching, Neural Networks, Hopfield Networks (H2)
Section: Hummel and Zucker Relaxation Papers (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Matching Using Tree Searching Techniques, Heuristic Search (H2)
Section: Shmuel Peleg Theoretical Relaxation Papers (H3)
* Bit-vector Algorithms for Binary Constraint Satisfaction and Subgraph Isomorphism
* Linear Programming Approach to Max-Sum Problem: A Review, A
* Model Based Pose Estimation of Articulated and Constrained Objects
16 for Constraint Satisfaction
Constraint Satisfaction, Survey
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Algorithms for Constraint-Satisfaction Problems: A Survey
Contactless
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Touchless Palmprint, Contactless Palmprints (H2)
Context
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Context and Structure for Classification (H2)
Section: Context in Computer Vision (H2)
Section: Context, Fine-Grained Classification (H3)
Section: Fine-Grained Classification Using CNN, Convolutional Neural Networks (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Techniques for Model Guided Segmentation, Context in Segmentation (H1)
* Interpretation of Remotely Sensed Images in a Context of Multisensor Fusion
10 for Context
Continual Learning
Section: Continual Learning (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Contour Coding
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Contour Coding, Boundary Coding (H2)
Contour Completion
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Contour Completion, Subjective Contours (H3)
Contour Matching
Section: 2-D Contour Matching, Indexing or Hashing Techniques (H3)
Section: 2-D Region or Contour Matching (H2)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Contours Through a Sequence (H3)
Section: Hierarchical/Scale-Space Contour Matching and Descriptions (H3)
Section: Jigsaw Puzzle Solving, 2-D Region or Contour Matching (H3)
Section: Partial Contour Matching, Piecewise Segments (H3)
Section: Piecewise Segment Matching of Contours (H2)
Section: Region or Contour Invariants, Signatures, Metrics for Matching (H3)
Section: Region/Contour Matching, Accumulation Based (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Snakes, Matching Deformable Contours (H3)
Section: String Matching, Syntatic Matching (H3)
Section: Tracking Applied to Heart Images (H3)
Section: Tracking Deformable Shapes (H3)
15 for Contour Matching
Contour Tracing
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Contour Representation of Binary Images Using Run-type Direction Codes
Contourlet
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Contourlet Representations and Processing (H2)
Contours
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Optical Flow Along Contours (H2)
Section: Optical Flow Field Computations and Use (H)
Section: Surface and Shape from Contours or Silhouettes (H1)
Section: Waveform and Contour Analysis (H2)
Contrast Enhancement
Section: Contrast Enhancement (H2)
Section: Exposure Correction, Exposure Control (H3)
Section: Histogram Equalization, Image Enhancement, Contrast Enhancement (H3)
Section: Image Enhancement for Display, Printers, High Dimensional Visualization (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Contrast
Section: Contrast Enhancement (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Contrastive Learning
Section: Contrastive Learning (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Control Systems
Section: Control Systems, Feedback Control, Systems Analysis (H2)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Convective Storm
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Convective Storm Analysis, Weather Radar Applications (H4)
Convex Hull
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Convex Hull Algorithms and Convexity Analysis (H2)
Section: Convex Hull of Polygons (H3)
Convex Polygon
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* On Limit Properties in Digitization Schemes
Convexity
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Convex Hull Algorithms and Convexity Analysis (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Morphological Decomposition of 2-D Binary Shapes into Conditionally Maximal Convex Polygons
Convolution
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Implementation of Convolution and Smoothing Techniques (H3)
Convolutional Neural Network
Section: Convolutional Neural Network, CNN, Re-Identification Issues, Pedestrian Tracking (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Convolutional Neural Networks
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Convolutional Network, Deep Networks, Learning for Compressive Sensing (H3)
Section: Convolutional Neural Networks for Human Action Recognition and Detection (H4)
Section: Convolutional Neural Networks for Image Descriptions, Classification (H3)
Section: Convolutional Neural Networks for Object Detection and Segmentation (H4)
Section: Convolutional Neural Networks for Semantic Segmentation, CNN (H4)
Section: Convolutional Neural Networks, Design, Implementation Issues (H4)
Section: Data Hiding, Steganography, Adversarial Networks, Convolutional Networks, Deep Learning (H3)
Section: Fine-Grained Classification Using CNN, Convolutional Neural Networks (H4)
Section: Forgetting, Learning without Forgetting, Convolutional Neural Networks (H4)
Section: Graph Convolutional Neural Networks (H4)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Intrepretation, Explaination, Understanding of Convolutional Neural Networks (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Single View 3D Reconstruction, Convolutional Neural Networks, CNN (H3)
Section: Training Issues for Convolutional Neural Networks (H4)
20 for Convolutional Neural Networks
Cooperating Robots
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Coordinating Motion of Cooperative Mobile Robots Through Visual Observation
Copy Detection
Section: Image Copy, Duplicate Image Detection (H4)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Video Copy, Video Duplicate Detection (H4)
Copy Move
Section: Copy-Move Tamper Detection, Splicing, Forensics (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Copyright Protection
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Watermarks for Copyright, Ownership Protection, Authentication, Verification (H2)
Coral Reef
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Coral Reef Mapping, Analysis (H2)
Corn Classification
Section: Maize or Corn Crop Analysis, Production, Detection, Health, Change (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Corn Yield
Section: Maize or Corn Crop Analysis, Production, Detection, Health, Change (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Cornea
Section: Eye, Cornea, Corneal Images (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Corneal Images
Section: Eye, Cornea, Corneal Images (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Corner Detection
Definition:* Locating the discontinuities in smooth curves, especially used to create polygonal representations of curves. Also detecting 2-D features where, roughly speaking, one quadrant of the region around the point differs from the other three.
Section: Corner Feature Detection Techniques and Use (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Direct Curvature Scale Space: Theory and Corner Detection
Corner Detector
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Corner Feature Detection Techniques and Use (H3)
Section: Curvature, Corners, Dominant Points, Salient Points, Junctions (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Assessing the performance of corner detectors for point feature tracking applications
* Local Symmetries of Digital Contours from Their Chain Codes
* Role of Key-Points in Finding Contours, The
* Steerable-Scalable Kernels for Edge Detection and Junction Analysis
* Volumetric Model and 3D Trajectory of a Moving Car from Monocular TV Frames Sequence of a Street Scene
12 for Corner Detector
Corner Detector, Evaluation
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Corner Detection Using the Facet Model
Corner Matching
Section: Image Registration -- Using Edges, Lines, Curves, and Corner and other Features (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Coronary Artery
Section: Medical Applications -- Coronary Arteries, Carotid Arteries (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Coronary Vessels
Section: Medical Applications -- Coronary Arteries, Carotid Arteries (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Correlation Filter
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Target Tracking Techniques, Filter Techniques, Correlation (H3)
Correlation Matching
Section: Canonical Correlation Analysis (H3)
Section: Correlation Based and Signal Matching Techniques (H2)
Section: Matching for Stereo, Correlation (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Cortex
Section: Brain Waves, EEG Analysis, Electroencephalogram for Biometrics (H3)
Section: Brain, Cortex, Alzheimer's Disease (H3)
Section: Brain, Cortex, Brain Waves, EEG Analysis, Electroencephalogram (H2)
Section: Brain, Cortex, Dementia (H2)
Section: Brain, Cortex, MRI Analysis, Models, 3-D (H2)
Section: Brain, Cortex, MRI Segmentation (H3)
Section: Brain, Cortex, Registration, Alignment, MRI, Other (H3)
Section: Brain, Parkinson's Disease (H2)
Section: Brain, Schizophrenia (H2)
Section: Brain, Stroke, Ischemic Stroke (H2)
Section: Medical Applications -- Brain, Cortex Applications (H1)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: White Matter Fiber Tractography MRI (H3)
* Cortical Surface Reconstruction Using a Topology Preserving Geometric Deformable Model
14 for Cortex
Cosine Transform
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Cosine Transform, DCT Compression (H2)
Section: DCT Block Coding -- Block Artifacts in DCT (H4)
Section: DCT Computation (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Cotton
Section: Cotton, Analysis and Change (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Count Objects
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Counting Instances, Counting Objects (H3)
Counting People
Section: Counting People, Crowds, Crowd Counting (H4)
Section: Counting People, Transportation System Monitoring, Queues (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Multi-Modal Crowd Counting (H4)
Section: Multi-Scale, Scale Aware Crowd Counting (H4)
Counting
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Counting Instances, Counting Objects (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Vehicle Counting (H3)
Covariance Propagation
Section: Books, Collections, Overviews, General, and Surveys (H)
* Propagating Covariance in Computer Vision
Covid
Section: GIS: for COVID Specific Tracking, Spread, Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pneumonia, Lung Analysis, Flu, COVID (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Crack Detection
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Defect Detection, Crack Detection (H3)
Section: Inspection -- Pavement, Road Surface, Asphalt, Concrete (H4)
Cracks
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Markov Fusion of a Pair of Noisy Images to Detect Intensity Valleys
Crater Detection
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Crater Detection, Impact Craters, Depressions (H3)
CRF
Definition:* Conditional Random Fields.
Cricket
Section: Baseball, Cricket, Tracking, Desctiptions, Analysis (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Crime Data
Section: GIS: Crime Data Analysis and Representation (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
CrisisMMD Dataset
* *CrisisMMD Dataset
Section: OCR, Document Analysis and Character Recognition Systems (H)
Crop Classification
Section: Classification for Crops, Analysis of Production, Specific Crops, Specific Plants (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Crop Residue
Section: Crop Residue Analysis (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Crop Yield
Section: Classification for Crops, Analysis of Production, Specific Crops, Specific Plants (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Cropland Abandonment
Section: Cropland Abandonment, Change Due to Abandonment (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Crops
Section: Aquaculture, Analysis, Extraction (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Cross-Domain
Section: Domain Adaption, Cross-Domain, Learning, Re-Identification Issues (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Cross-Modal Biometrics
Section: Biometrics, Cross-Modal, Multi-Modal Systems, Multibiometrics, Combined Face and Other Features, Fusion (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Cross-Modal Counting
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Multi-Modal Crowd Counting (H4)
Cross-Modal Fusion
Section: Fusion, General Multi-Modal (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Cross-Modal Retrieval
Section: Cross-Modal Indexing, Cross-Modal Retrieval (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Cross-Modal
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Multi-Modal, Cross-Modal Captioning, Image Captioning (H3)
Cross Calibration
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Cross-Calibration for Radiometric Calibration (H3)
Crosswalks
Section: Crosswalk Detection, Zebra Crossings (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Crowd Behavior
Section: Human Activities, Crowds, Lots of People (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Crowd Counting
Section: Counting People, Crowds, Crowd Counting (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Multi-Modal Crowd Counting (H4)
Section: Multi-Scale, Scale Aware Crowd Counting (H4)
Crowds
Section: Crowds, Tracking Multiple People, Multiple Pedestrian Tracking (H4)
Section: Detecting Anomalies, Abnormal Behavior In Crowds (H4)
Section: Human Activities, Crowds, Lots of People (H4)
Section: Human Activities, Tourist Traffic Flow (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Crowdsource
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Estimating Regional Snow Line Elevation Using Public Webcam Images
Crowdsourced
Section: GIS: Volunteered Geographic Information, Open Access, Crowd Sourcing, Crowdsource (H2)
Section: GIS: Volunteered Geographic Information, OpenStreetMap, Open Street Map (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Crowdsourcing
Section: Crowdsourcing, Recognition, Analysis, Descriptions (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Crowdsourcing in Computer Vision
Crowns
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Tree Crowns, Crown Shape, Crown Delineation (H3)
Cruise Control
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Adaptive Cruise Control (H4)
Section: Car Following Control, Leader-Follower Control (H4)
Section: Overtaking Analysis, Control (H4)
CRULE
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Novel Approach to Colour Constancy, A
Cryptography
Section: Encryption, Visual Cryptography, Authentication (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
CT
Section: Heart, Cardiac, Angiography using CAT, CT, Tomography (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Tomographic Image Generation, CAT, CT, Reconstruction (H2)
Section: Tomographic Images, CAT Scans (Computed Axial Tomography) (H1)
Section: Tomographic Images, CAT, CT, Overviews, Surveys, Datasets (H2)
Section: Tomographic Object Construction, Object Extraction, Analysis, Organs (H2)
Cultural Heritage
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Archeological Sites, Modeling, Analysis, Tools (H2)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Cultural Heritage Modeling Systems, Laser, LiDAR (H3)
Section: Cultural Heritage Models, General Systems, Modeling Systems (H3)
Section: Cultural Heritage Sites, Modeling, Analysis, Large Scale Models (H2)
Section: Cultural Heritage Sites, Modeling, Specific Models: Europe (H3)
Section: Cultural Heritage, Museum Visitation Models, Immersive, Augmented Reality, Virtual Reality (H4)
Section: Cultural Heritage, Museum Visitation Models, Tour Guide, Visualization (H3)
Section: Ground Penetrating Radar for Archeological Sites (H3)
Section: Historical Document Analysis, Ancient Documents (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Specific 3-D Models, Cultural Items, Applied 3-D Descriptions (H2)
Section: Specific 3-D Models, Paintings, Murals, Frescoes (H2)
Section: Specific 3-D Models, Rock Art, Petroglyphs, Rock Structures, Caves (H2)
Section: Specific 3-D Models, Vaulted Structures (H3)
Section: Specific Museum Visitation Models, Tour Guide, Visualization (H4)
* ISHIGAKI Retrieval System Using 3D Shape Matching and Combinatorial Optimization
19 for Cultural Heritage
Curb Detection
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Curb Detection, Street Boundaries (H3)
Curcuit Inspection
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Chips, Wafers, PCB, PWB, VLSI, IC, Disks, etc. (H3)
Curls
Section: Enhancement, Restoration of Document Images, Curls (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Currency
Section: Money and Check Processing -- Amounts, etc. (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Currents
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Downwelling, Upwelling Analysis, Oceans, Lakes, Water (H4)
Section: Ocean Currents, Costal Surface Currents (H3)
Section: Oceanic Eddy Currents, Eddies (H4)
Cursive Character Recognition
Section: Cursive Script, Word Level Recognition, Word Spotting, Language Model (H4)
Section: Handwriting, Cursive Script Recognition Systems (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: On-Line Cursive Script Recognition Systems (H4)
Cursive Script
Section: OCR, Document Analysis and Character Recognition Systems (H)
* On-Line Cursive Word Recognition System, An
* Recognizing Off-Line Cursive Handwriting
Curvature Analysis
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Curvature and Features of Surfaces and Range Data (H2)
Section: DEM, Surface Analysis for Ridges and Streams, Rivers, Drainage, Depressions (H2)
Curvature Three-Dimensional
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Generic Curvature Features from 3-D Images
Curvature
Section: Curvature, Corners, Dominant Points, Salient Points, Junctions (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Features for Contour Matching (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Curvature, Surfaces
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Curvature and Features of Surfaces and Range Data (H2)
Curve Description
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Local Symmetries of Digital Contours from Their Chain Codes
Curve Evolution
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Active Contours, Snakes or Deformable Curves (H2)
Section: Snakes, Algorithms for Computation (H3)
Section: Snakes, Applications (H3)
Section: Snakes, General Techniques and Descriptions (H3)
Section: Snakes, Restricted Curves, Splines, etc. (H2)
Curve Fitting
Section: Curve Fitting (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Curve Partitions
Section: Basic Algorithms to Partition Curves, Represent Curves (H2)
Section: Basic Algorithms to Partition Curves, The Early Days (H2)
Section: Curve Partitions, Applied to Chain Codes (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Generation of Straight Line Segments or Curve Partitions (H1)
Section: Parallel Algorithms, Curve Partition (H3)
Curve Representations
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Generalized Uniqueness Wavelet Descriptor for Planar Closed Curves, The
Curve Segmentation
Section: Basic Algorithms to Partition Curves, Represent Curves (H2)
Section: Basic Algorithms to Partition Curves, The Early Days (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Curvelet
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Curvelet Transform (H2)
Curves, General
Section: Curve Fitting (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: General Systems for Lines and Curves (H2)
Cut Detection
Section: Cut Detection in Compressed Images, MPEG, Video Analysis (H4)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Video Analysis, Cut Detection, Scene Segmentation, Shot Detection, Shot Boundary (H3)
Cyanobacteria
Section: Cyanobacteria, Analysis, Detection (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Cybersickness
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Section: Three Dimensional Displays, Viewer Fatigue, Sickness, Comfort, Aesthetics (H2)
Cyclic Motion
Section: Cyclic Motion, Periodic Motion, Symmetric, for Walking and Gait Recognition (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Walking, Gait Recognition, University of Southampton (H4)
* Cyclic Motion Detection for Motion Based Recognition
Cyclone
Section: Cyclones, Hurricanes, Typhoons, Radar, Cloud analysis (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Cylinders
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Cylinders, Application Tanks (H3)
Section: Generalized Cylinders, Medial Axis Descriptions (H1)