LADAR
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: Laser Sensors for Range, Time of Flight (H3)
Section: LIDAR, LADAR -- Range data (H2)
* Model-Based Automatic Target Recognition (ATR) System for Forward-Looking Groundbased and Airborne Imaging Laser Radars (Ladar)
LAI
Section: LAI, Leaf Area Index, Land Cover Analysis (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Lake Ice Detection
Section: Lake and River Ice Detection (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Lake Level
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Reservoir Monitoring, Reservoir Usage, Water Level, Lake Level (H2)
Lakes
Section: Glacial Lake Monitoring (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Land Cover
Section: Changes using Landsat Images (H4)
Section: Global-Scale Analysis, Global Land Cover Analysis (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, General Problems, Remote Sensing (H1)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Water, Water Body Detection Using SAR (H2)
11 for Land Cover
Land Cover, Urban
Section: Classification for Urban Area Land Cover, Remote Sensing (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Land Degradation
Section: Land Degradation (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Land Mines
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Ground Penetrating Radar, UXO, Landmines, Explosives (H4)
* Polarimetric processing of coherent random noise radar data for buried object detection
* Ultrawideband Radar Images of the Surface Disturbance Produced by a Submerged, Mine-Like Object
Land Use Change
Section: Land Use Change Analysis (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Land Use
Section: Land Use Change Analysis (H3)
Section: Land Use, General Problems (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Landfill Site
Section: Landfill Sites, Site Selection, Analysis (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Landform
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landform Analysis, Landform Description (H3)
Landing
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Aircraft Landings, Spacecraft Landing (H4)
Landmark Detection
Section: Anotomical Landmark Detection, Landmark Location in Various Sensors (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Landmark Location
Section: Anotomical Landmark Detection, Landmark Location in Various Sensors (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Landmarks
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Face Analysis, Facial Landmarks (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Localization, Georeference, Urban Regions, City Models, Building Models (H4)
Section: Navigation, Landmarks (H3)
Section: Qualitative Navigation, Drop Off, Where in the World or Region (H4)
* Visual Navigation for a Mobile Robot Using Landmarks
7 for Landmarks
Landmines
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Ground Penetrating Radar, UXO, Landmines, Explosives (H4)
LandSat
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Changes using Landsat Images (H4)
Section: Fusion of LANDSAT or Sentinel Images (H4)
Section: Land Surface Temperature using LandSat (H3)
Section: Radiometric Calibration of LandSat Scanners, Images, Cross-Calibration (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
7 for LandSat
Landsat, History
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Landsat Program: Recent History and Prospects, The
* Science of Landsat Analysis Ready Data
Landslide Laser
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Analysis, LiDAR, Laser Scanner (H4)
Landslide LiDAR
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Analysis, LiDAR, Laser Scanner (H4)
Landslide Risk
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Susceptibility, Landslide Risk Analysis, Hazards (H4)
Landslide SAR
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Analysis, SAR, InSAR, IFSAR, Radar (H4)
Landslide Susceptibility
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Analysis, Earthquake Related, Seismic Analysis (H4)
Section: Landslide Susceptibility, Landslide Risk Analysis, Hazards (H4)
Landslide
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Detection, Analysis, Damage Assessment, Deformations (H3)
Section: Specific Site Landslide Analysis (H4)
Landslides
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Landslide Analysis, Earthquake Related, Seismic Analysis (H4)
Lane Changing
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Changing, Lane-Change, Analysis, Control (H4)
Lane Departure
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Departure Detection, Lane Keeping, Lane Control Assistance (H4)
Lane Detection
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Departure Detection, Lane Keeping, Lane Control Assistance (H4)
Section: Lane Detection, Lane Following, White Line Detection (H3)
Lane Following
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Departure Detection, Lane Keeping, Lane Control Assistance (H4)
Section: Lane Detection, Lane Following, White Line Detection (H3)
Lane Keeping
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Departure Detection, Lane Keeping, Lane Control Assistance (H4)
Section: Lateral Control for Vehicles (H4)
Lane Markings
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Road Marking Detection, Visible, LiDAR (H3)
Language Analysis
Section: Authorship Issues (H4)
Section: Grammar Based Analysis, Language Issues, Natural Language (H3)
Section: Language Translation, Grammar Based Analysis (H4)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Social Media Processing (H4)
Section: Steganalysis for Text, Documents (H3)
7 for Language Analysis
Language Recognition
Section: Language Recognition, Multi-Language Documents (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Language Vision Model
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Vision-Language Models, Language-Vision Models, VQA (H4)
Laparoscopy
Section: Laparoscopy, Surgery (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Large-Scale Stereo
Section: Large Scale Multi-View Stereo, Internet Scale, Many Views (H2)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Large Baseline Stereo
Section: Matching for Stereo, Wide Baseline Matching Issues (H3)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Large Displacement Flow
Section: Large Displacement Optical Flow (H2)
Section: Optical Flow Field Computations and Use (H)
Large Scale Database
Section: Image Databases, Large Scale Systems, Web-Scale System (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Large Scale Systems, Web-Scale System, Learning, Neural Nets (H4)
Laser Range Finders
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Laser Sensors for Range, Time of Flight (H3)
Laser Scanner
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Road Following, Depth, Stereo Based, Off-Road, Safe Path (H3)
Laser Scanners
Section: Buildings from Depth Data, LiDAR Data (H2)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Laser
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: Calibration -- LiDAR, Laser Scanner, Depth Sensor, Scanner Error Analysis (H3)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Forest Analysis, Terrestrial Laser Scanner, Terrestrial LiDAR, TLS (H4)
Section: Shape from Laser Ranging and Structured Light Images (H1)
LASSO Regression
Section: Group LASSO, Trace LASSO (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Latent Fingerprints
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Latnet Fingerprint Recognition, Analysis (H3)
Lateral Control
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lateral Control for Vehicles (H4)
Lava
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Lava Flows, Eruptions Volcanoes, Thermal (H4)
Section: Monioring Mt. Etna (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Layout Analysis
Section: Document Layout, Document Segmentation, Page Layout, Structure Analysis (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Layout to Image
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Text to Image, Layout to Image, Image Based Rendering (H3)
Layout
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Room Layout (H4)
LBP
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Face Analysis, Local Binary Patters for Face Recognition (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Local Binary Patterns, LBP, Point Features (H3)
Section: Local Binary Patterns, LPB for Texture (H3)
Section: Local Features, LBP, Patterns, for Pedestrian Detection, People Detection (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
7 for LBP
LDA
Definition:* Linear Discriminant Analysis.
Section: Discriminant Analysis (H3)
Section: Invariants -- Linear Discriminant Analysis, Fisher Linear Discriminant (H3)
Section: LDA in Face Recognition (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)
Leaf Area Index
Section: LAI, Leaf Area Index, Land Cover Analysis (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Leaf Nitrogen
Section: Leaf Nitrogen, Crop Nitrogen (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Leaf Shape
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Plants, Leaf Shapes, Leaf Analysis, Leaf Segmentation (H4)
Learning Models
Section: Learning Model Descriptions (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Learning
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: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Contrastive Learning (H2)
Section: Convolutional Neural Networks for Human Action Recognition and Detection (H4)
Section: Data Hiding, Steganography, Adversarial Networks, Convolutional Networks, Deep Learning (H3)
Section: Deep Learning Facial Expression Recognition (H4)
Section: Deep Network Training, Learning, Strategy, Design, Techniques (H4)
Section: Deep Networks, Deep Learning for Human Action Recognition (H4)
Section: Deep Neural Networks, Deep Learning for Super Resolution (H4)
Section: Domain Adaption, Cross-Domain, Learning, Re-Identification Issues (H4)
Section: Emotion Recognition, Deep Learning (H4)
Section: Evaluation and Analysis of Learning Techniques (H2)
Section: Face Expression Recognition Using Learning, Neural Nets (H4)
Section: Face Recognition Systems Using Neural Networks, Learning (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Generative Adversarial Network, Neural Networks for Super Resolution (H3)
Section: Human Posture, or Human Pose, Learning, Neural Networks (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: Incremental Learning for Human Action Recognition (H4)
Section: Inpainting, GAN, CNN, Neural Nets, Learning (H4)
Section: Land Cover Change Analysis Using Learning, Neural Nets (H3)
Section: Large Scale Systems, Web-Scale System, Learning, Neural Nets (H4)
Section: Learning -- Conference Listing (H2)
Section: Learning Face Detection, Neural Nets, SVM (H3)
Section: Learning for Detecting Anomalies (H4)
Section: Learning for High Dynamic Range Generation (H4)
Section: Learning for Image Quality Evaluation, CNN, GAN (H3)
Section: Learning for Principal Components, Eigen Representations (H3)
Section: Learning for Super Resolution (H3)
Section: Learning in Computer Vision (H1)
Section: Learning in Computer Vision (H3)
Section: Learning Object Descriptions, Object Recognition (H2)
Section: Learning, General Non-Vision Learning Issues (H2)
Section: Learning, General Surveys, Overviews (H2)
Section: Learning, Neural Nets for Coding, Compression in Video (H2)
Section: Learning, Neural Nets for Human Detection, People Detection, Pedestrians (H4)
Section: Learning, Neural Networks for Single Image Super Resolution (H4)
Section: Masked Image Modeling (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Meta-Learning (H3)
Section: Models, Inference, Learning Human Activities, Human Behavior (H4)
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: Motion Segmentation, Neural Networks, Learning (H4)
Section: Multi-Object Tracking, Neural Networks, Learning (H4)
Section: Multiple Instance Learning (H2)
Section: Neural Network Guided Background Subtraction, Learning Methods (H4)
Section: Neural Networks and Learning for Human Action Recognition and Detection (H4)
Section: Neural Networks for Noise Removal, Denoising, Restoration (H2)
Section: Neural Networks, Learning for Image Compression (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Opeical Flow, Learning, Neural Networks, GAN (H2)
Section: Optical Flow Field Computations and Use (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Perceptual Grouping, Saliency, Neural Networks, Learning (H3)
Section: Privacy in Learning (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Self-Supervised Learning for Object Detection and Segmentation (H3)
Section: Self-Supervised Learning (H2)
Section: Single View 3D Reconstruction, Learning (H3)
Section: Tracking People, Re-Identification Issues, Learning (H4)
Section: Tracking using Neural Nets, Learning (H3)
Section: Unbalanced Datasets, Imbalanced Sample Sizes, Imbalanced Data, Long-Tailed Data (H3)
* Face Recognition with Learning Machines
* Hidden Tree Markov Models for Document Image Classification
* Learning Structural Descriptions from Examples
* Learning Texture-Discrimination Masks
* Optimizing Learning in Image Retrieval
* RIEVL: Recursive Induction Learning in Hand Gesture Recognition
* Some Experiments in Applying Inductive Inference Principles to Surface Reconstruction
75 for Learning
Least Median
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Least Median of Squares Based Robust Analysis of Image Structure
Least Significant Bit
Section: Data Hiding, Steganography, LSB, Least Significant Bit (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Least Squares
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: Least Squares Applied to Restoration (H2)
* Sequential Coordinate-Wise Algorithm for the Non-negative Least Squares Problem
Left Luggage
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Unattended Package, Abandoned Luggage, Left Luggage, Theft (H4)
Left Ventricle
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)
Legged Locomotion
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Legged Locomotion Robots, Assistants (H3)
Lens Distortion
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Lens Distortion, Aberration, Radial Distortion, Internal Parameters (H2)
* Calibration of Stereo Cameras Using a Non-Linear Distortion Model
* Efficient and Accurate Camera Calibration Technique for 3-D Machine Vision, An
Leukemia
Section: Blood Cell Cancers, Lymphoma, Leukemia (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Leukocyte
Section: Blood Cells, Counting, Extraction, Analysis (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Levee Monitoring
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Dam Analysis and Monitoring, Levee Analysis, Deformation, Erosion (H4)
Level Set Methods
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Optical Flow Field Computations and Use (H)
* Image-Processing: Flows under Min/Max Curvature and Mean-Curvature
* Level Set Methods: Evolving Interfaces in Geometry, Fluid Mechanics, Computer Vision and Materials Science
Level Set
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: Level Set Models for Volumes (H3)
Section: Level Set Segmentation, Level Set Methods (H2)
Section: Level Sets, Medical Image Segmentation (H3)
Section: Level Sets, Shape Models, Prior Shape Models (H3)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* new time dependent model based on level set motion for nonlinear deblurring and noise removal, A
8 for Level Set
Libraries
Section: Document Retrieval Systems, Databases and Issues, Libraries (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)
License Plate Recognition
Section: License Plate Recognition, Extraction, Analysis (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Large-scale privacy protection in Google Street View
License Plates
Section: License Plate Recognition, Extraction, Analysis (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
LiDAR Calibration
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Calibration -- Laser Scanner Multi-Path, Multipath (H4)
Section: Calibration -- LiDAR, Laser Scanner, Depth Sensor, Scanner Error Analysis (H3)
Section: Laser Scanner Calibration -- Calgary Group, Lichti (H4)
Section: RGB-D Laser Scanner Calibration, Color and LIDAR (H4)
Lidar Inpainting
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Inpainting, Inpainting Range Images, Range, Depth Data (H4)
LiDAR Odometry
Section: LiDAR Odometry, Distance Measurments from LiDAR (H3)
Section: Optical Flow Field Computations and Use (H)
Lidar Registration
Section: ICP, Iterative Closest Point Registeration for Point Clouds (H4)
Section: Register Point Cloud Data, Point Cloud Matching, Laser Scanner Data (H4)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: RGB-D Registeration, RGBD Registraion, Color and LiDAR (H4)
LiDAR
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: Biomass Measurements, Forest, LiDAR Techniques, Airborne Laser (H4)
Section: Biomass Measurements, Forest, Terrestial Laser Techniques, TLS (H4)
Section: Buildings from Depth Data, LiDAR Data (H2)
Section: Buildings from Terrestrial Laser Data, Mobile Scanners, Ground-Based LiDAR (H3)
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: Cultural Heritage Modeling Systems, Laser, LiDAR (H3)
Section: DEM, DSM, DTM, Generation Using LiDAR, LIDAR, Laser Data (H2)
Section: Denoising, Range Images, Range, Depth Data (H4)
Section: Forest Analysis, Canopy Heights, LiDAR (H4)
Section: Forest Analysis, Depth, LiDAR, Laser Scanner (H4)
Section: Fusion, Range or Depth and Intensity or Color Data (H3)
Section: Laser Sensors for Range, Time of Flight (H3)
Section: LiDAR for Aerosols, Aerosol Optical Depth, Air Quality (H4)
Section: LiDAR for Land Cover, Laser Scanners for Land Cover, Remote Sensing (H2)
Section: Localization, LiDAR, Laser, Depth, 3D Data, Range Based (H4)
Section: Obstacles, Objects on the Road Using Radar, Sonar, LiDAR, Active Vision (H4)
Section: Point Cloud Change Detection, Registration (H4)
Section: Radiometric Calibration of Laser Scanners, LIDAR (H3)
Section: Range Data, Point Cloud Processing and Analysis (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Road Following, Depth, Stereo Based, Off-Road, Safe Path (H3)
Section: Road Marking Detection, Visible, LiDAR (H3)
26 for LiDAR
LiDAR, Change Detection
Section: Point Cloud Change Detection, Registration (H4)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
LiDAR, Roads
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Road Extraction in Radar, SAR, Lidar, Laser, Depth (H2)
Lie Groups
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Dominant-Subspace Invariants
Lifelog
Section: Lifelog, Daily Activities (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Lifting Operator
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Wavelet Lifting Operator, Transform (H4)
Light Field
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Light Field Cameras, Images, and Analysis (H2)
Section: Light Field Compressed Sensing (H3)
Section: Light Field Depth Estimation (H3)
Section: Light Field Rendering (H4)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Super Resolution for Light Field Images and Data (H3)
8 for Light Field
Light Source Direction
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Light Source Detection, Light Source Estimation (H2)
Section: Light Source Direction Computations, Illumination Information, Illuminant (H3)
* Estimation of Illuminant Direction, Albedo, and Shape from Shading
Lightfield
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Light Field Cameras, Images, and Analysis (H2)
Lighting Model
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Lighting Effects, View Generation, Graphics Issues (H3)
Lighting
Section: Face Analysis, Shading, Illumination, Lighting and Color Variations (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Lightness
Section: Color Constancy, Retinex (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Lightning
Section: Lightning Detection, Analysis (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Lightweight Super Resolution
Section: Lightweight Super Resolution (H3)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Line Adjacency Graph
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Run-Length Coding Representations and Operations (H2)
Line Approximation
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Generation of Straight Line Segments or Curve Partitions (H1)
Line Detection
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Hueckel -- Basis Functions, Model Fitting for Edge Detection (H2)
Section: Line Detectors, Direct Detection of Straight Lines (H2)
Section: Road Following, Road Tracking Systems, Connecting Fragments, Extracting Fragments (H2)
Section: Road Junctions, Road Intersections (H2)
Section: Road Network Detection, Road Extraction Systems (H1)
* Mathematical Models for Automatic Line Detection
8 for Line Detection
Line Drawings
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Creation of Line Drawings, Detection of Wireframes (H2)
Section: Shape from Line Drawings, Junction Labeling (H1)
Section: Surface and Shape from Contours or Silhouettes (H1)
* Extraction of the Line Drawing of 3-Dimensional Objects by Sequential Illumination from Several Directions
Line Drawings, Analysis
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Line Drawing Analysis, Wireframes (H2)
Line Drawings, Shape
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Creation of Line Drawings, Detection of Wireframes (H2)
Section: Shape from Line Drawing, Shape from Lines (H2)
Line Features
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Calibration Using Line Features, Lines (H3)
Line Following
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Lane Detection, Lane Following, White Line Detection (H3)
Line Labeling
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Line Labeling Techniques (H2)
Section: Shape from Line Drawings, Junction Labeling (H1)
Line Labels
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Extracting a Valid Boundary Representation from a Segmented Range Image
Line Matching
Section: 2-D Line Segments with 2-D Structure (H2)
Section: 2-D Lines with 3-D Structure (H2)
Section: 3-D Lines with 3-D Structure (H2)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Line of Sight
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Visibility Analysis, Sight Lines, Line of Sight (H3)
Line Segments
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: Generation of Straight Line Segments or Curve Partitions (H1)
Section: Line Detectors, Direct Detection of Straight Lines (H2)
* Bayesian Method for Fitting Parametric and Nonparametric Models to Noisy Data, A
Line Vectorization
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Line Vectorization, Document Analysis (H2)
Linear Constraints
Section: Optical Flow Field Computations and Use (H)
* Performance of Camera Translation Direction Estimators from Optical-flow: Analysis, Comparison, and Theoretical Limits, The
Linear Discriminant Analysis
Section: Discriminant Analysis (H3)
Section: Invariants -- Linear Discriminant Analysis, Fisher Linear Discriminant (H3)
Section: LDA in Face Recognition (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)
Linear Embedding
Section: Locally Linear Embedding, Nonlinear Embedding (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Linear Features
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Extended Linear Features - Beyond Segments (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Line Vectorization, Document Analysis (H2)
* Approach to the Recognition of Contours and Line-Shaped Objects, An
Linear Prediction
Section: Linear Prediction Techniques (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Linear Programming
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Linear Programming Approach fo the Weighted Graph Matching Problem, A
Lines
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Digital Geometry -- Lines, Curves and Contours (H3)
Lines, Colinear
Section: Colinear Line Segments (Collinear) (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Lines, General
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: General Systems for Lines and Curves (H2)
Linkoping Univ.
* *Linkoping University
Lip Detection
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Mouth Location, Lip Location, Detection (H3)
Lip Reading
Section: Combined Audio Visual Recognition and Analysis (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Lipreading, Lip Reading, Lip Tracking (H2)
Lipreading
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Lipreading, Lip Reading, Lip Tracking (H2)
Lithology
Section: Geologic Mapping, Geology Analysis, Mineralogy, Fault Zones (H1)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Liveness
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Liveness Detection, Spoofing, Fingerprint Recognition (H3)
Section: Liveness Detection, Spoofing, Presentation Attack, Faces, Other Biometrics (H3)
Liver Disease
Section: Liver Disease, Tomography, CAT Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Local Binary Patterns
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Face Analysis, Local Binary Patters for Face Recognition (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Local Binary Patterns, LBP, Point Features (H3)
Local Features
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Local Features, Computation, Analysis (H3)
Localization
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Action Localization, Action Localisation (H4)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Audio Source Separation, Source Localization, Direction of Arrival, DoA, Analysis (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Iris Detection, Segmentation and Localization Systems (H3)
Section: Localization, Georeference, Urban Regions, City Models, Building Models (H4)
Section: Localization, GPS Assisted, GNSS Assisted, Guidance System Assisted, Other Annotation (H4)
Section: Localization, LiDAR, Laser, Depth, 3D Data, Range Based (H4)
Section: Localization, RFID Tags (H4)
Section: Localization, Where is the robot, Where is the camera (H3)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: Object Localization (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Source Localization, Direction of Arrival, DoA, Analysis (H2)
* more you learn, the less you store: Memory-controlled incremental SVM for visual place recognition, The
17 for Localization
Localization, Indoor
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Indoor Localization, Navigation Issues, Non-Image, Wi-Fi, Phone Positioning (H4)
Section: Indoor Navigation Issues, Lines, Walls, Doors, Flat Surfaces (H3)
Locally Linear Embedding
Section: Locally Linear Embedding, Nonlinear Embedding (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Log-Polar Sensor
Section: Optical Flow Field Computations and Use (H)
* On the Estimation of Depth from Motion Using an Anthropomorphic Visual Sensor
Log-Polar
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Complex Log Mapping, Algorithms and Sensors (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Optical Flow Field Computations and Use (H)
* Binocular Fusion Revisited Utilizing a Log-Polar Tessellation
* Direct Computation of the Focus of Expansion from Velocity Field Measurements
* Disparity Estimation on Log-Polar Images and Vergence Control
7 for Log-Polar
Log Mapping
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Complex Log Mapping, Algorithms and Sensors (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Optical Flow Field Computations and Use (H)
* Complex Logarithmic Mapping and the Focus of Expansion
* Direct Computation of the Focus of Expansion
* Direct Estimation of Time-to-Impact from Optical Flow
* Geometric invariance in space-variant vision systems: The exponential chirp transform
* Motion Stereo Using Ego-Motion Complex Logarithmic Mapping
* On the Advantage of Polar and Log-Polar Mapping for Direct Estimation of Time-to-Impact from Optical Flow
* Position, Rotation and Scale Invarient Optical Correlation
12 for Log Mapping
Log Polar Mapping
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Segmentation of Frame Sequence Obtained by a Moving Observer
Logo Recognition
Section: Analysis of Graphics, Logos (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Analysis of Compressed Document Images for Dominant Skew, Multiple Skew, and Logotype Detection
* Applying Algebraic and Differential Invariants for Logo Recognition
* Neural Based Architecture for Spot-Noisy Logo Recognition, A
* Shape-Based Retrieval: A Case-Study with Trademark Image Databases
* Trademark Shapes Description by String-Matching Techniques
* Using Negative Shape Features for Logo Similarity Matching
9 for Logo Recognition
Logs
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Lumber, Logs, Wood (H3)
Long-Tailed Data
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Unbalanced Datasets, Imbalanced Sample Sizes, Imbalanced Data, Long-Tailed Data (H3)
Long Sequence
Section: Long Sequence Matching and Motion (H2)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Long Short-Term Memory
Section: LSTM: Long Short-Term Memory for Captioning, Image Captioning (H3)
Section: LSTM: Long Short-Term Memory (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Longwave Radiation
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Upward Longwave Radiation, Outgoing Longwave Radiation, Upwelling Radiation (H4)
Loop Closure
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Loop Closure, Simultaneous Localization and Mapping (H3)
Loss Functions
Section: Loss Functions, Triplet Loss Function, Deep Learning, Neural Netowrks (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Lossless Compression
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Lossless Coding, Lossless Compression, Transmission (H2)
* Lossless Compression of AVIRIS Images by Vector Quantization, The
Low-Rank Representation
Section: Human Action Recognition, Sparse Techniques, Low-Rank, SVM (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Low Bit Rate Coding
Section: Computing Very Low Bitrate, 3-D and Object Based Coding (H4)
Section: High Rate Compression, Low Bit Rate Compression, Region Based Coding (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion Compensation, Block, Region, Object, and Low Bit Rate Coding (H2)
Section: Motion Compensation, Low Bit Rate, Survey, Evaluations (H4)
Section: Very Low Bitrate, 3-D and Object Based Coding (H4)
Low Dose CT
Section: Few Views, Limited Views, Low Dose, Tomographic Image Reconstruction (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Low Light
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Low Light Enhancement (H3)
Section: Night Time Processing (H3)
Low Resolution
Section: Face Recognition at a Distance, In the wild, In-the-Wild, Low Resolution Faces (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
LSB
Section: Data Hiding, Steganography, LSB, Least Significant Bit (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
LSTM
Section: LSTM: Long Short-Term Memory for Captioning, Image Captioning (H3)
Section: LSTM: Long Short-Term Memory (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Luggage Inspection
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Surveillance Systems, Applied to Baggage Inspection, Cargo Inspection (H3)
Lumber
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Lumber, Logs, Wood (H3)
Lunar Terrain
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Moon, Lunar Terrain, Lunar Analysis, Martian Terrain (H2)
Lunar
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Moon, Lunar Terrain, Lunar Analysis, Martian Terrain (H2)
Lung Cancer
Section: Lungs, and Lung Cancer Image Analysis (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Lung Nodules
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pulmonary Nodules, Lung Nodules (H3)
Lungs
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Airway Tree Structure (H3)
Section: Bronchoscopy Systems, Bronchial Analysis (H3)
Section: Emphysema, Lung Analysis (H3)
Section: Lung Motion Analysis, Respiration, Breathing (H3)
Section: Lungs, and Lung Cancer Image Analysis (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pneumonia, Lung Analysis, Flu, COVID (H3)
Section: Pulmonary Nodules, Lung Nodules (H3)
Section: Thorax, Thoracic Analysis (H3)
* Rotation invariant features based on three dimensional Gaussian Markov random fields for volumetric texture classification
11 for Lungs
Lymph Nodes
Section: Medical Applications -- Lymph Nodes (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Lymphoma
Section: Blood Cell Cancers, Lymphoma, Leukemia (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)