Packet Video
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Transmission Issues, Internet, Packet Video (H3)
Page Segmentation
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Document Layout, Document Segmentation, Page Layout, Structure Analysis (H3)
Section: Form and Layout Analysis (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Page Segmentation, General Evaluations (H4)
* Multilevel Training of Binary Morphological Operators
* Page Segmentation and Zone Classification: The State of the Art
7 for Page Segmentation
Pain
Section: Face Expression Recognition for Pain (H4)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Paintings
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Specific 3-D Models, Paintings, Murals, Frescoes (H2)
* Image Separation With Side Information: A Connected Auto-Encoders Based Approach
Palm Trees
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Palm Trees, Oil Palms, Trees as Crops (H4)
Palm Vein
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Vein Structure in Palm, Hands, Recognition, Systems (H2)
Palmprint
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Palmprints, Recognition, Systems (H2)
Section: Touchless Palmprint, Contactless Palmprints (H2)
Pan-Sharpening
Section: Evaluation, Quality Assissment Pansharpening (H4)
Section: Pansharpening, Fusion of Aerial Images (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Pancreas
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pancreatic Disease, CAT Analysis (H3)
Pancreatic Disease
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pancreatic Disease, CAT Analysis (H3)
Panoptic Segmentation
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Panoptic Segmentation (H3)
Panorama
Section: Augmented Reality, With Panoramic, Omnidirectional Images (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Panoramic Image
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Panoramic Image, Panorama Creation (H3)
Panoramic Sensors
Section: Catadioptric Cameras (H4)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Omnidirectional and Panoramic Sensors (H3)
* N-Ocular Stereo for Real-Time Human Tracking
Panoramic Views
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: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Shape and Stereo from Panoramic Views, Stereo from Omnidirectional Images, Plenoptic (H1)
* Feature Matching in 360^o Waveforms for Robot Navigation
* Omni-directional Stereo for Making Global Map
* Real-Time Generation of Environmental Map and Obstacle Avoidance Using Omnidirectional Image Sensor with Conic Mirror
* Telepresence by Real-Time View-Dependent Image Generation from Omnidirectional Video Streams
8 for Panoramic Views
Pansharpening
Section: Evaluation, Quality Assissment Pansharpening (H4)
Section: Pansharpening, Fusion of Aerial Images (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Parallel Algorithms
* *Parallel Computer Vision
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Applied Parallel Systems and Algorithms (H2)
Section: Computation of General Features (H1)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Edge Detection, Computation Techniques for Speed (H3)
Section: Fast, Parallel, Multiresolution Techniques for the Computation of Skeletons (H2)
Section: General Parallel, Multi-Processor or Multicore, Algorithms (H2)
Section: Hardware Implementations, FPGA, Image Processing (H3)
Section: Hardware, VLSI Implementations, Embedded Processors, Sensor Processing (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-Processor Algorithms, Connection Machine, Hypercube (H2)
Section: Multi-Processor Algorithms, Multi-Core, Cellular, Systolic (H2)
Section: Multi-Processor Algorithms, Pyramid Machines (H2)
Section: Optical Flow Field Computations and Use (H)
Section: Parallel and Multi-Processor Algorithms, General, Survey (H2)
Section: Parallel Optic Flow Computation, Efficient Computation (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Reconfigurable Mesh Architectures and Algorithms (H3)
* Building a Quadtree and Its Applications on a Reconfigurable Mesh
* Large-Scale Parallel Data Clustering
* Light speed labeling: efficient connected component labeling on RISC architectures
* Parallel Algorithm for Graph Matching and Its MASPAR Implementation, A
24 for Parallel Algorithms
Parallel Architectures
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Algorithms for Image Component Labeling on SIMD Mesh-Connected Computers
Parallel Systems
Section: Array Processors, Massive Parallel Systems, Pyramids (H2)
Section: Hardware -- Image Understanding Architecture, IUA (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Pipelined Processors and Algorithms (H2)
Parking Assistance
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Parking Assistance, Automatic Parking (H4)
Parking Surveillance
Section: Applied Traffic Surveillance, Traffic Events, Red Lights, Parking (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Parking
Section: Applied Traffic Surveillance, Traffic Events, Red Lights, Parking (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Parkinson's Disease
Section: Brain, Parkinson's Disease (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Part-Based
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Representation of Parts, Part-Based Models (H1)
Part Models
Section: Human Action Recognition, Part Models, Human Pose (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Part Segmentation
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Deformable Models for Segmentation (H2)
Section: Representation of Parts, Part-Based Models (H1)
Partial Egomotion Estimation
Section: Optical Flow Field Computations and Use (H)
* Detection of Independent Motion Using Directional Motion Estimation
Particle Filter
Definition:* Sequential Monte Carlo (SMC) technique to solve nonlinear state parameter estimation problems.
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Multi-Object, Multi-Target, Particle Filter Techniques (H3)
Section: Target Tracking Techniques, Particle Filter Techniques (H4)
Particle Filtering
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Multi-Object, Multi-Target, Particle Filter Techniques (H3)
Section: Target Tracking Techniques, Particle Filter Techniques (H4)
Particle Swarm
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Particle Swarm Tracking, Particle Swarm Optimization (H4)
Particulates
Section: Pollution, Black Carbon (H4)
Section: Pollution, Particulate, PM2.5, PM10 (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Parzen
Section: Fisher, Parzen, and Other Clustering Measures and Decompositions (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Pasture
Section: Biomass Evaluations Pasture, Grassland, Rangeland, Savanna (H4)
Section: Pasture, Grassland, Rangeland Analysis (H3)
Section: Pasture, Grassland, Rangeland, Change, Degradation, Temporal (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Trees in Pasture, Grassland, Rangeland, Savanna, Shrubs (H4)
Patch-Based
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Object Based Land Cover, Parcels, Region Based Land Cover, Land Use Analysis (H3)
Section: Patch-Based Restoration, Patch Based Denoising (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Patch Attack
Section: Adversarial Patch Attacks (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Patch Matching
Section: Region Properties for Matching (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Patch Models
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Generation or Representation of Surface Patches (H1)
Patch, Inpainting
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Inpainting, Patch Based Methods, Region Methods (H4)
Patches
Section: Multi-View Patch, Region Based Analysis (H2)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Path Planning
Section: Active Vision - Path Planning (H2)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: ALV, Autonomous Vehicles, Robotic Systems or Vehicles, Autonomous Robots (H2)
Section: Carnegie Mellon NAVLAB, AMBLER, etc. (H3)
Section: CMU Road Followers, ALVINN YARF MANIAC (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Obstacle Dectection, Objects on the Road (H3)
Section: Path Planning for Obstacle Avoidance (H4)
Section: Planning Robot (Manipulator) Positions (H3)
Section: Planning Sensor Position, View Selection, View Planning, Next View (H3)
Section: Planning Vehicle Position, Path Planning or Route Planning (H3)
Section: Road, Path Following Operators (H2)
Section: Traffic, Routing, Evaluation (H4)
Section: Transit Routing, Scheduling, Evaluation (H4)
Section: Travel Time, Evaluation (H4)
Section: UAV Path or View Planning, Next View (H4)
Section: Vehicle Control, Dickmanns (H3)
17 for Path Planning
Pathology
Section: Breast Cancer Cell Analysis, Pathology, Nuclei Detection (H3)
Section: Histopathology, Tissue Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Whole Slide Analysis, Histopahtology, Cells (H4)
Pattern Alignment
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Empirical Evaluation of Two Criteria for Pattern Comparison and Alignment
Pattern Classification
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Optimum Character Recognition System Using Decision Function, An
Pattern Recognition
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Classification Methods, Clustering for Region Segmentation (H2)
Section: Clustering, Pattern Recognition, General Issues (H2)
Section: Feature Selection in Pattern Recognition or Clustering (H2)
Section: K-Means Clustering (H2)
Section: King Sun Fu Pattern Recognition Papers (H2)
Section: Nearest Neighbor Classification (H2)
Section: Pattern Recognition Issues (H1)
Section: Pattern Recognition Systems (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Pattern Recognition, General and Survey Articles (H2)
Section: Sparse Feature Selection (H3)
Section: Statistical Learning, Clustering, Learning Feature Values (H2)
* Advances in Statistical Pattern Recognition
* Artificial Intelligence Approach to Pattern Recognition: A Perspective and an Overview, The
* Introduction to Statistical Pattern Recognition
* Pattern Classification
* Pattern Classification and Scene Analysis
* Pattern Recognition: Human and Mechanical
20 for Pattern Recognition
Pavement Analysis
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Pavement, Road Surface, Asphalt, Concrete (H4)
PBMPlus
* *pbmplus Image File Format Conversion Package
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
PCA Computation
Section: Computation and Analysis of Principal Components, Eigen Values, SVD (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
PCA
Definition:* Principal Component Analysis.
Section: Computation and Analysis of Principal Components, Eigen Values, SVD (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: ICA, PCA in Face Recognition (H4)
Section: Invariants -- Principal Component Analysis (H3)
Section: Learning for Principal Components, Eigen Representations (H3)
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: PCA, Principal Component Analysis, Data Dimensionality Reduction (H3)
Section: Surveys, Comparisons, Evaluations, Principal Components (H3)
* efficient model order selection for PCA mixture model, An
* Extensions of LDA by PCA mixture model and class-wise features
* Gabor-based kernel PCA with fractional power polynomial models for face recognition
13 for PCA
PCB 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)
PCB
Definition:* Printed Circuit Board.
PDE
Definition:* Partial Differential Equation.
Section: Books, Collections, Overviews, General, and Surveys (H)
* Mathematical Problems in Image Processing Partial Differential Equations and the Calculus of Variations
Peatland Classification
Section: Peatland, Analysis and Change (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Pedestrian Attributes
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Pedestrian Attributes, Pedestrian Descriptions (H4)
Pedestrian Behavior
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Pedestrian Safety Issues, Pedestrian Behavior (H4)
Pedestrian Detection
Section: HoG, Gradients, Histogram of Gradients for Human Detection, People Detection, Pedestrians (H4)
Section: Human Detection, People Detection, Pedestrians, Locating (H3)
Section: Human Detection, People Detection, Pedestrians, Using Depth, Stereo (H4)
Section: Learning, Neural Nets for Human Detection, People Detection, Pedestrians (H4)
Section: Local Features, LBP, Patterns, for Pedestrian Detection, People Detection (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Motion Based Human Detection, Spatio-Temporal Analysis, Pedestrians (H4)
Section: Pedestrian Attributes, Pedestrian Descriptions (H4)
8 for Pedestrian Detection
Pedestrian Safety
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Pedestrian Safety Issues, Pedestrian Behavior (H4)
Pedestrian Tracking
Section: Crowds, Tracking Multiple People, Multiple Pedestrian Tracking (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Pedestrian Trajectory Analysis, Pedestrian Tracking (H4)
Section: Tracking People, Human Tracking, Pedestrian Tracking (H3)
Pedestrian Trajectory
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Pedestrian Trajectory Analysis, Pedestrian Tracking (H4)
Pedestrian
Section: Crosswalk Detection, Zebra Crossings (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Pedestrian Safety Issues, Pedestrian Behavior (H4)
Pedestrians
Section: Counting People, Transportation System Monitoring, Queues (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Peer to Peer
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Peer-to-Peer Video Transmission, Streaming, P2P (H4)
People
Section: Database Issues, Finding People (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Perceptrons
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Computer Recreations
Perceptual Grouping
* 3D Descriptions of Buildings from an Oblique View Aerial Image
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: 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: Contour Completion, Subjective Contours (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Grouping, Figure-Ground, Background, Foreground (H2)
Section: Grouping, Lines and Curves (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Optical Illusions (H3)
Section: Perceptual Grouping, Perceptual Organization Techniques, Saliency (H1)
Section: Perceptual Grouping, Saliency, General Systems (H2)
Section: Perceptual Grouping, Saliency, Neural Networks, Learning (H3)
Section: Perceptual Grouping, Saliency, Theory (H2)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Detecting Runways in Aerial Images
* Detection of Buildings from Monocular Views of Aerial Scenes Using Perceptual Grouping and Shadows
* Detection of Buildings Using Perceptual Groupings and Shadows
* Dynamic System for Object Description and Correspondence, A
* Inferring Surfaces from Images
* Integrating Vision Modules: Stereo, Shading, Grouping, and Line Labeling
* Linear Feature Extraction
* Model-Driven Grouping and Recognition of Generic Object Parts from a Single Image
* Normalized Cuts and Image Segmentation
* Parallel Technique for Signal-Level Perceptual Organization, A
* Pattern Recognition by Machine
* Perceptual Grouping with Applications to 3D Shape Extraction
* Recovery of the Three-Dimensional Shape of and Object from a Single View
* Segmentation of Textured Images and Gestalt Organization Using Spatial/Spatial-Frequency Representations
* Use of Monocular Groupings and Occlusion Analysis in a Hierarchical Stereo System
* What Makes a Good Feature?
34 for Perceptual Grouping
Perceptual Organization
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Perceptual Grouping, Saliency, Theory (H2)
Perceptual Quality
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Image Quality Evaluation, Human Visual System Based, HVS (H3)
Section: Image Quality Evaluation, Perceptual Quality, Subjective Quality (H3)
Performance Analysis
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Empirical Evaluation of Neural, Statistical and Model-based Approaches to FLIR ATR
* Handprinted Word Recognition on a NIST Data Set
* Model-based Reconstruction of Multiple Circular and Elliptic Objects from a Limited Number of Projections
* Structure Learning of Bayesian Networks By Genetic Algorithms: A Performance Analysis of Control Parameters
* Towards Effective Planar Shape Representation with Multiscale Digital Curvature Analysis Based on Signal-processing Techniques
10 for Performance Analysis
Performance Capture
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Performance Capture, Capture for Animation (H4)
Performance Evaluation
Section: Computer Vision Workshops -- Performance, Evaluation, Benchmarks (H3)
Performance
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Performance Characterization in Computer Vision (H3)
Section: Performance, Evaluation Issues (H2)
* Performance Characterization in Image Analysis: Thinning, a Case in Point
Perimeter
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Computing Area, Diameter and Perimeter (H3)
Periocular Biometrics
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Periocular Biometrics (H3)
Periodic Textures
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Texture Periods Description (H2)
Permafrost
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Tundra Regions, Permafrost Analysis (H2)
Persian
Section: Farsi, Persian Character Recognition (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Persistent Scatter
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: SAR, InSAR, Surface Deformation with Persistent, Permanent Scatter (H4)
Person Search
Section: Actor Identification (H3)
Section: Database Issues, Finding People (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Personal Photos
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Relevance Feedback, Personal Photo Collections (H4)
Personal Videos
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Personal Videos, Consumer Videos, Abstracts, Synopsis, Summarization (H4)
Personality
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Personality, Traits, Mood, Deception, Diagnosis Analysis (H4)
Perspective Effects
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Shape and Structure from Perspective Effects, Vanishing Points, Detection (H1)
Perspective, Camera Calibration
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Perspective Based, Vanishing Points (H2)
PET
Definition:* Positron Emission Tomography.
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Positron Emission Tomography -- PET (H2)
Section: Positron Emission Tomography, Fessler Group Papers (H3)
Section: Positron Emission Tomography, PET Image Reconstruction (H3)
Petroglyphs
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)
Ph.D.
* 3D Scene Modeling And Understanding From Image Sequences
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: 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)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (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: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (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: OCR, Document Analysis and Character Recognition Systems (H)
Section: Optical Flow Field Computations and Use (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)
* Adaptive and Integrated Multimodal Sensing and Processing Framework For Long-Range Moving Object Detection and Classification, An
* Adaptive Texture Description and Estimation of the Class Prior Probabilities for Seminal Quality Control
* Algorithms for selecting parameters of combination of acyclic adjacency graphs in the problem of texture image processing
* Approximate Ensemble Methods for Physical Activity Recognition Applications
* Automatic Information and Safety Systems for Driving Assistance
* Automatic Segmentation of Anatomical Structures using Deformable Models and Bio-Inspired/Soft Computing
* Bioinspired metaheuristics for image segmentation
* Colour constancy in natural images through colour naming and sensor sharpening
* Detecting and indexing moving objects for Behavior Analysis by Video and Audio Interpretation
* Dynamic Obstacle Detection of Road Scenes using Equi-Height Mosaicking Image
* Exploiting Multimedia Content: A Machine Learning Based Aproach
* Fuzzy Multilevel Graph Embedding for Recognition, Indexing and Retrieval of Graphic Document Images
* Interactive and audience-adaptive information interfaces
* Methods for text segmentation from scene images
* Monitoring and Diagnosing Neonatal Seizures by Video Signal Processing
* Monocular Depth Cues in Computer Vision Applications
* Multi-class learning for vessel characterisation in intravascular ultrasound
* Multimodal Stereo from Thermal Infrared and Visible Spectrum
* Noise modeling and depth calibration for Time-Of-Flight cameras
* Optical Flow in Driver Assistance Systems
* Overcomplete Image Representations for Texture Analysis
* Parallel Framework for Video Super-resolution, A
* Polyp Localization and Segmentation in Colonoscopy Images by Means of a Model of Appearance for Polyps
* Registration and analysis for images couple: Application to mammograms
* Retinal Image Analysis Oriented to the Clinical Task
* Robust human detection through fusion of color and infrared video
* Semantic Awareness for Automatic Image Interpretation
* SWT voting-based color reduction method for detecting text in natural scene images
* Towards an interactive index structuring system for content-based image retrieval in large image databases
48 for Ph.D.
Pharmaceutical Inspection
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Pharmaceutical Applications, Drugs, Pills (H3)
Phase-Based
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Modeling Foreshortening in Stereo Vision using Local Spatial Frequency
Phase Coding
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Phase Coding Patterns (H2)
Phase Correlation
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Empirical Evaluation of Two Criteria for Pattern Comparison and Alignment
Phase Differences
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Fast Computation of Disparity from Phase Differences, The
Phase Retrieval
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Phase Retrieval (H2)
Phase Unwraping
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Phase Unwrapping, Stereo Depth unwrapping (H2)
Phased Array Radar
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Phased Array Radars, Analysis, Use (H3)
Phenotyping
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Plant Phenotyping (H4)
Phoenix
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Phoenix Image Segmentation System: Description and Evaluation, The
* Recursive Region Segmentation by Analysis of Histograms
Phone Application
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Gesture Systems, Mobile Devices, Phones (H4)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Phone, Mobile, Applications and Implementations (H3)
Phone Data
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Traffic Flow Analysis Using Phone Signals, Cell Data, Wi-Fi data (H4)
Phone Location
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Indoor Localization, Navigation Issues, Non-Image, Wi-Fi, Phone Positioning (H4)
Phone Usage
Section: Driver Monitoring, Mobile Phone Usage (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Phone
Section: Hand-Held Camera Reconstruction, Phone Based Reconstruction, Shape from Motion (H2)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Photoacoustic Tomography
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Photoacoustic Tomography, Ultrasonic, Generation (H2)
Photobook
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Photobook: Tools for Content-Based Manipulation of Image Databases
Photogrammetry
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Photogrammetric, Bundle Adjustment, Block Adjustment (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Photogrammetry, Books on Photogrammetry (H1)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Comparison of Two Image Compression Techniques for Softcopy Photogrammetry, A
Photometric Calibration
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Photometric Calibration, Radiometric Calibration, Spectral Calibration, Color Calibration (H2)
Photometric Stereo
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Albedo, Reflectance Map from Multiple Images (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Interreflections, Reflections (H2)
Section: Light Source Detection, Light Source Estimation (H2)
Section: Non-Lambertian Photometric Stereo (H2)
Section: Photometric Stereo, Multiple Views, Multiview (H2)
Section: Shape from Multiple Light Sources, Photometric Stereo (H1)
Section: Shape Using Color Images, Color Photometric Stereo (H2)
* Appearance Characterization of Linear Lambertian Objects, Generalized Photometric Stereo, and Illumination-Invariant Face Recognition
* empirical study on the effects of translucency on photometric stereo, An
11 for Photometric Stereo
Photometric Stereo, Four Lights
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Extracting the Shape and Roughness of Specular Lobe Objects Using Four Light Photometric Stereo
Photoplethysmography
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Photoplethysmography, Heart Rate, Pulse Rate Analysis, Vital Signs, Non-Contact Methods (H3)
Photovoltaic Energy
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Solar Energy Analysis, Photovoltaic Analysis, Buildings, Roofs (H3)
Phubber
Definition:* Someone who repeatedly looks at their phone.
Physics Based Vision
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: Deformable Solids -- Pentland Papers (H2)
Section: Deformable Solids -- Terzopoulos Papers (H2)
Section: Physics Based Vision (H1)
* Closed-Form Solutions for Physically Based Shape Modeling and Recognition
* Nonrigid Motion Analysis Using Nonlinear Finite Element Modeling
* Physically Based Analysis of Deformations in 3D Images
8 for Physics Based Vision
Piecewise Linear
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Piece-Wise Linear Representations from Curves (H3)
Pipeline Processors
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Phone, Mobile, Applications and Implementations (H3)
Section: Pipelined Processors and Algorithms (H2)
Pipes
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Solder Joints, Welding, Pipes (H3)
Pixel Difference
Section: Data Hiding, Steganography, Pixel Difference (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Planar Motion.
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Understanding Object Motion
Planar Patches
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Planar Patches from Range, Planar Surfaces (H2)
Plankton
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Plankton Analysis, Extraction, Features, Small Scale and Large Scale (H4)
Planning
Section: Active Vision - Path Planning (H2)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Active Vision, Visual Attention (H2)
Section: Camera Position, Sensor Position for Model Generation (H3)
Section: Planning Optimal Sensor Positions, Optimal View Planning, Optimal Next View (H4)
Section: Planning Robot (Manipulator) Positions (H3)
Section: Planning Sensor Position, View Selection, View Planning, Next View (H3)
Section: Planning Vehicle Position, Path Planning or Route Planning (H3)
Section: Visibility Analysis, Sight Lines, Line of Sight (H3)
9 for Planning
Plant Disease
Section: Plant Disease Analysis, General Plant Diseasses (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Plant Inspection
Section: Agriculture, Inspection -- Food Products, Plants, Farms (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection of Food Grains (H4)
Plant Leaf
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Plants, Leaf Shapes, Leaf Analysis, Leaf Segmentation (H4)
Plant Nitrogen
Section: Leaf Nitrogen, Crop Nitrogen (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Plant Phenotyping
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Plant Phenotyping (H4)
Plaque
Section: Arteries, Plaque Formation, Detection, Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Plastic Litter
Section: Plastic Litter, Ocean Plastic, Beach Litter (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Plastic Mulch
Section: Greenhouse Detection, Plastic Mulch Detection and Analysis (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Platoon
Section: Mixed Traffic, Platoon, Autonmous Controls, Intersections, Signals (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Platooning
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Platoons, Platooning, Groups, Formation, Vehicle Control, Vehicle Cooperation (H4)
Section: Security, Network Defense, Platoons, Platooning, Formation (H4)
Section: Vehicle Swarms, Robot Swarms (H4)
Platoons
Section: Connected Vehicles, Use, Evaluation (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Player Tracking
Section: Human Activities, Sports, Player Tracking (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Plenoptic
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)
Plethysmography
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Photoplethysmography, Heart Rate, Pulse Rate Analysis, Vital Signs, Non-Contact Methods (H3)
pLSA
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: Probabilistic Latent Semantic Analysis, pLSA. (H3)
* Image categorization via robust pLSA
PM2.5
Section: Pollution, Particulate, PM2.5, PM10 (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Pneumonia
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pneumonia, Lung Analysis, Flu, COVID (H3)
Point Cloud Classification
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Point Cloud Classification, Recognition (H3)
Point Cloud Completion
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Depth Completion, Point Cloud Completion (H4)
Point Cloud Compression
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Point Cloud Compression (H3)
Point Cloud Denoising
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Denoising, Range Images, Range, Depth Data (H4)
Point Cloud Generation
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Point Cloud Generation, Point Cloud Synthesis (H4)
Point Cloud Processing
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Point Cloud Processing for Neural Networks, Convolutional Neural Networks (H3)
Section: Range Data, Point Cloud Processing and Analysis (H3)
Point Cloud Quality
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Point Cloud Quality (H4)
Point Cloud Recognition
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Point Cloud Classification, Recognition (H3)
Point Cloud Registration
Section: 3-D Surface Registration for Mosaics and Models (H4)
Section: ICP, Iterative Closest Point Registeration for Point Clouds (H4)
Section: Register Point Cloud Data, Point Cloud Matching, Laser Scanner Data (H4)
Section: Registration or Multiple Range Images, Range Image Registration (H4)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Point Cloud Segmentation
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Depth Object Segmentation, Point Cloud Segmentation (H3)
Section: Instance Segmentation, Point Cloud Segmentation (H3)
Point Cloud Synthesis
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Point Cloud Generation, Point Cloud Synthesis (H4)
Point Cloud Tracking
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Multi-Target Tracking with Multiple Sensors, Stereo, Depth, Range (H4)
Point Cloud Up-Sample
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Point Cloud Up-Sampling (H3)
Point Cloud
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Mesh Representations from 3D Point Clouds (H4)
Point Clouds
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Fusion, Range or Depth and Intensity or Color Data (H3)
Section: ICP, Iterative Closest Point Registeration for Point Clouds (H4)
Section: Point Cloud Rendering (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)
7 for Point Clouds
Point Correspondences
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Randomized Polygon Search for Planar Motion Detection
Point Matching
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Points with 2-D Structures, Point Matching, Features (H2)
Section: 2-D Points with 3-D Structures (H2)
Section: 3-D Points with 3-D Structures (H2)
Section: Closest Point Algorithms, ICP, Iterative Closest Point (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Visually Estimating Workpiece Pose in a Robot Hand Using the Feature Points Method
7 for Point Matching
Pointing Gestures
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Pointing Gestures, Pointing Systems (H3)
Poisson Noise
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Poisson Noise Removal (H3)
Polar Representation
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Versatile Machine Vision System for Complex Industrial Parts, A
Polarimetric
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Polarimetric Interferometric SAR, PolInSar (H3)
Section: PolSAR, Polarimetric, Polarimetry, Radar Polarization (H3)
Polarization
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Polarization Effects, Polarized Light (H2)
* Polarization/Radiometric Based Material Classification
* Shape from Polarization Images
Polarized Light
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: Polarization Effects, Polarized Light (H2)
* Target Detection in Optically Scattering Media by Polarization-Difference Imaging
PolInSAR
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Polarimetric Interferometric SAR, PolInSar (H3)
Pollen
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Pollen Detection, Analysis (H4)
Pollution
Section: Aerosols, Aerosol Optical Depth, Air Quality, Specific Sites (H3)
Section: Air Quality, Air Pollution, Aerosols, General Pollution (H3)
Section: LiDAR for Aerosols, Aerosol Optical Depth, Air Quality (H4)
Section: Pollution, Methane Measurements, CH4, Other Hydrocarbons (H4)
Section: Pollution, Ozone Measurements, O3 (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
PolSAR
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: PolSAR, Polarimetric, Polarimetry, Radar Polarization (H3)
PolSAR/K
* .">PolSAR/
* .">PolSAR/
Polygon Matching
Section: 2-D Region or Contour Matching (H2)
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: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Polygon
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: General Polygonal Representations and Computations (H3)
Polygonal Approximation
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Polygonal Representations of Curves (H3)
* Computer Recognition of Handwritten Numerals by Polygonal Approximations
Polygonal Decomposition
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Polygonal Decomposition Techniques (H4)
Polygonal Description
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Polygonal Representations of Curves (H3)
Polygonal Patches
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Polygonal Surface Patch Models (H3)
Polyp
Section: Medical Applications -- Colonoscopy, Polyp Detection, Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Pooling
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Pooling in Convolutional Neural Networks Implementations (H4)
Population Data
Section: GIS: Popultaion Data, Distributions, Analysis (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Portrait Editing
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Face Image Editing, Portrait Editing, Interactive Editing (H4)
Pose Estimation
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Object Recognition from Pose Estimation or Alignment (H2)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: 6D Object Pose Estimation (H4)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Grimson Object Recognition Papers (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (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)
* ARGOS Image Understanding System, The
* Automatic Model Construction and Pose Estimation from Photographs Using Triangular Splines
* Automatic Registration Method for Frameless Stereotaxy, Image Guided Surgery and Enhanced Reality Visualization, An
* Complex EGI: A New Representation for 3-D Pose Determination, The
* Estimating 3-D Rigid-Body Transformations: A Comparison of Four Major Algorithms
* Geometric neurocomputing for pattern recognition and pose estimation
* Inverse Perspective Problem from a Single View for Polyhedra Location, The
* New Efficient and Direct Solution for Pose Estimation Using Quadrangular Targets: Algorithm and Evaluation, A
* Object Recognition and Pose Determination in Multi Sensor Robotic Systems
* Perspective Angle Transform and Its Application to 3-D Configuration Recovery
20 for Pose Estimation
Pose Estimation, Accumulation
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pose Estimation, 3D Models (H3)
Pose Estimation, Evaluation
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Pose Estimation from Corresponding Point Data
* Pose Refinement: Application to Model Extension and Sensitivity to Camera Parameters
Pose Estimation, Hough
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pose Estimation, 3D Models (H3)
Pose Estimation, Lines
Section: Line Based Matching for Pose Estimation (H2)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Pose Estimation, Perspective
Section: Line Based Matching for Pose Estimation (H2)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Pose Estimation, Points
Section: Point Based Pose Estimation and Recognition (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Pose Estimation, Range Data
Section: Pose Estimation -- Range Data (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Pose Tracking
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Human Pose Recognition from Video, Pose from Motion (H3)
Section: Human Pose Tracking, Posture Tracking, Posture from Video, Pose from Motion (H3)
Pose
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Human Action Recognition and Detection Using Human Pose (H4)
Section: Human Pose from Depth, 3-D Data, Stereo, Multi-View Data (H3)
Section: Human Pose from Silhouettes (H3)
Section: Human Posture, or Human Pose, Human Body Pose (H2)
Section: Human Posture, or Human Pose, Learning, Neural Networks (H3)
Section: Human Posture, or Human Pose, Transformers, ViT (H3)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Multi-Person Human Pose Desicriptions (H3)
9 for Pose
Pose, Head
Section: 3-D Model Based Head Motion, Head Tracking, 3D Data Head Pose (H2)
Section: Face Pose, Head Pose from Stereo, Multi-View, Depth, or Range Data (H3)
Section: Face Pose, Head Pose (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Positron Emission Tomography
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Positron Emission Tomography -- PET (H2)
Section: Positron Emission Tomography, Fessler Group Papers (H3)
Section: Positron Emission Tomography, PET Image Reconstruction (H3)
Postal Codes
Section: Numbers, Digits, Zip (Postal) Codes (H4)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Posture
Section: Animation and Reconstruction of Human Model from Posture, or Pose (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Human Posture and Shape, Clothing Related (H3)
Section: Human Posture, or Human Pose, Human Body Pose (H2)
Section: Human Posture, or Human Pose, Learning, Neural Networks (H3)
Section: Human Posture, or Human Pose, Transformers, ViT (H3)
Section: Human Posture, Upper Body Posture, Arms (H3)
7 for Posture
Potato
Section: Potato Crop Analysis, Production, Detection, Health, Change (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Power Line Detection
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Power Line Extraction, Powerline Extraction, Radar, SAR, Lidar, Laser, Depth (H2)
Power Lines
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Insulators on Power Lines, Transmission Towers, Pylons (H3)
Power Tower
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Transmission Towers, Pylons, Poles, Extraction, Radar, SAR, Lidar, Laser, Depth (H3)
PPG
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Photoplethysmography, Heart Rate, Pulse Rate Analysis, Vital Signs, Non-Contact Methods (H3)
PPP
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: GPS, GNSS, Precise Point Positioning (H4)
Pre-training
Section: CLIP, Contrastive Language-Image Pre-Training (H4)
Section: Fine Tuning, Fine-Tuning, Pre-Training, Zero-Shot, One-Shot (H3)
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)
Section: Pre-Training (H2)
Precipitable Water Vapor
Section: Atmospheric, Water Vapor, Precipitable Water Vapor, PWV (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Precipitation
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Evaluation and Comparison of Rainfall Analysis over China (H4)
Section: Evaluation and Comparison of Rainfall Analysis, Rain, Precipitation Products (H4)
Section: Rainfall Analysis, Rain, Precipitation, Satellite Based Systems (H4)
Section: Rainfall Analysis, Rain, Precipitation, Weather Radar (H3)
Precise Point Positioing
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: GPS, GNSS, Precise Point Positioning (H4)
Precision Agriculture
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Precision Agriculture Tools (H4)
Prediction
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Prediction for Tracking Techniques (H4)
Section: Target Tracking Techniques, Prediction, Trajectory Based (H4)
Section: Traffic Flow Prediction, Forecast (H4)
Presentation Attack
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Liveness Detection, Spoofing, Presentation Attack, Faces, Other Biometrics (H3)
Price
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Pricing Issues in Charging (H4)
Primal Sketch
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)
* Curvature Primal Sketch, The
* Implicit Constraints of the Primal Sketch, The
* Representation and Recognition of the Spatial Organization of Three-Dimensional Shapes
* Representing Visual Information: A Computational Approach
* Topographic Classification of Digital Image Intensity Surfaces Using Generalized Splines and the Discrete Cosine Transform
7 for Primal Sketch
Primary Production
Section: Gross Primary Production, Net Primary Production, GPP, NPP (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Principal Component Analysis
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: PCA, Principal Component Analysis, Data Dimensionality Reduction (H3)
Principal Components
Section: Computation and Analysis of Principal Components, Eigen Values, SVD (H3)
Section: Fisher, Parzen, and Other Clustering Measures and Decompositions (H2)
Section: ICA, PCA in Face Recognition (H4)
Section: Invariants -- Principal Component Analysis (H3)
Section: Learning for Principal Components, Eigen Representations (H3)
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: Surveys, Comparisons, Evaluations, Principal Components (H3)
8 for Principal Components
Print Quality
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Paint and Printing Quality, Print Analysis (H3)
Printed Characters
Section: Handwritten Characters, Roman, Latin Alphabet (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Privacy Protection
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Surveillance Systems, Privacy Protection, Issues, Techniques, Face Obscuration (H3)
Privacy
Section: Biometrics, Privacy Issues, Security Issues (H3)
Section: Face De-Identification, Privacy (H3)
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: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Privacy in Learning (H3)
Section: Privacy in Vehicle Networks, VANET (H4)
7 for Privacy
Privacy, Surveillance
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Surveillance Systems, Privacy Protection, Issues, Techniques, Face Obscuration (H3)
Probabilistic Causal Model
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Diagnostic Reasoning Based on a Genetic Algorithm Operating in a Bayesian Belief Network
Probability Density Estimation
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Data-driven Procedure for Density-Estimation with Some Applications, A
Probability
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Evidence Theory, Combination Techniques, Optimization Techniques (H3)
Section: Fuzzy Sets, Fuzzy Logic (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Decision Theory and Artificial Intelligence: I. A Semantics Based Region Analyzer
* On Optimally Combining Pieces of Information, with Application to Estimating 3-D Complex-Object Position from Range Data
* Probability-Based Control for Computer Vision
8 for Probability
Profile
Section: Face Analysis, Profiles (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Progressive Transmission
Section: Hierarchical, Multi-Level, Pyramidal Coding Techniques (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Image Transmission Issues, Progressive Transmission -- Still Images (H3)
Projection Learning
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Projection Learning (H3)
Projective Analysis
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Shape and Structure from Perspective Effects, Vanishing Points, Detection (H1)
Projector
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Projector-Camera Systems, Camera-Projector Systems, Projection onto Surface (H3)
Proposals
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Object Proposals, Initial Points, Proto-Objects, Candidates (H3)
Prostate Cancer
Section: Medical Applications -- Prostate Cancer Analysis (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Prosthesis
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Rehabilitation Systems, Prosthesis Systems, Control (H4)
Protein
Section: Extraction and Analysis of Proteins (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Proximity Matrix
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Modal Approach to Feature-Based Correspondence
* Modal Matching for Correspondence and Recognition
Pruning
Section: Neural Net Pruning (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
PSF
Definition:* Point Spread Function.
Psychophysical Evidence
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Defect Detection in Random Color Textures
Ptychographic
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Ptychographic, Fourier Ptychographic, Ptycho-Tomography (H3)
Public Safety
Section: Carried Objects, Carrying Objects (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Unattended Package, Abandoned Luggage, Left Luggage, Theft (H4)
Pullution
Section: Pollution, Black Carbon (H4)
Section: Pollution, CO2 Measurements, Carbon Dioxide, Carbon Monoxide (H4)
Section: Pollution, Greenhouse Gasses (H4)
Section: Pollution, NOx Measurements, Nitric, Nitrous Oxide, Nitrogen Oxides (H4)
Section: Pollution, Particulate, PM2.5, PM10 (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Pulmonary Nodules
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pulmonary Nodules, Lung Nodules (H3)
Pulse Rate
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Photoplethysmography, Heart Rate, Pulse Rate Analysis, Vital Signs, Non-Contact Methods (H3)
* Demonstration of a Remote Optical Measurement Configuration That Correlates With Breathing, Heart Rate, Pulse Pressure, Blood Coagulation, and Blood Oxygenation
Pushbroom Camera
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Pushbroom Camera Calibration Issues (H3)
Pylons
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Transmission Towers, Pylons, Poles, Extraction, Radar, SAR, Lidar, Laser, Depth (H3)
Pyramid Structure
* 2-D Object Recognition Using Hierarchical Boundary Segments
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Multi-level, Multi-Scale Segmentation and Smoothing Methods (H2)
Section: Pyramid Representations (H2)
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)
* Chamfering: A fast method for obtaining approximations of the Euclidean distance in N dimensions
* Distributed Processing for Multiresolution Dynamic Scene Analysis
* Laplacian Pyramid as a Compact Image Code, The
* Line Connectivity Algorithms for an Asynchronous Pyramid Computer
* Multiprocessor Pyramid Architectures for Bottom-Up Image Analysis
* Processing of Line Drawings in a Hierarchical Environment
* Pyramid Algorithm for Fast Curve Extraction, A
* Pyramidal Stereovision Algorithm Based on Contour Chain Points, A
18 for Pyramid Structure
Pyramid Structures, Matching
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Pyramidal Algorithms for Iconic Indexing
Pyramid Technique
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Coarse-Fine Bimodality Analysis of Circular Histogram
Pyramid
Section: Optical Flow -- Hierarchical, Pyramid, Multi-Grid, Multi-Scale Approaches (H2)
Section: Optical Flow Field Computations and Use (H)
Pyramid, Laplacian
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Laplacian Pyramid as a Compact Image Code, The
Pyramids
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Hierarchical, Multi-Level, Pyramidal Coding Techniques (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Multi-Scale, Pyramid Texture Segmentation Approaches (H2)
* Border Delineation in Image Pyramids by Concurrent Tree Growing
* Hierarchical Data Structure for Picture Processing, A
* Hierarchical Line Extraction
* Layered Recognition Cone Networks That Preprocess Classify and Describe
* Object Detection in High Resolution Multispectral Images
* On Curve Approximation And Hierarchical Hough Transform
* Structured Computer Vision: Machine Perception through Hierarchical Computational Structures
16 for Pyramids