Page Segmentation
* OCR, Document Analysis and Character Recognition Systems (H)
* Page Segmentation, General, Evaluations (H4)
* Page Segmentation and Zone Classification: The State of the Art
Pan-Sharpening
* Image and Sensor Fusion for Cartography and Aerial Images (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Panoramic Sensors
* Catadioptric Cameras (H4)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Omnidirectional and Panoramic Sensors (H3)
* N-Ocular Stereo for Real-Time Human Tracking
Panoramic Views
* 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Shape and Stereo from Panoramic Views (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
Parallel Algorithms
* *Parallel Computer Vision
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Applied Parallel Systems and Algorithms (H2)
* Computation of General Features (H1)
* Fast, Parallel, Multiresolution Techniques for the Computation of Skeletons (H2)
* General Parallel and Multi-Processor Algorithms (H2)
* Hardware, VLSI Implementations, Processors, Sensor Processing (H2)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Multi-Processor Algorithms, Cellular, Systolic (H2)
* Multi-Processor Algorithms, Connection Machine, Hypercube (H2)
* Multi-Processor Algorithms, Pyramid Machines (H2)
* Optical Flow Field Computations and Use (H)
* Parallel and Multi-Processor Algorithms, General, Survey (H2)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Real-Time, Parallel Optic Flow Computation (H2)
* Reconfigurable Mesh Architectures and Algorithms (H3)
* Building a Quadtree and Its Applications on a Reconfigurable Mesh
* Large-Scale Parallel Data Clustering
* Parallel Algorithm for Graph Matching and Its MASPAR Implementation, A
20 for Parallel Algorithms
Parallel Architectures
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Algorithms for Image Component Labeling on SIMD Mesh-Connected Computers
Parallel Systems
* Array Processors, Massive Parallel Systems, Pyramids (H2)
* Hardware -- Image Understanding Architecture, IUA (H2)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Pipelined Processors and Algorithms (H2)
Part Segmentation
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Deformable Models for Segmentation (H2)
Partial Egomotion Estimation
* Optical Flow Field Computations and Use (H)
* Detection of Independent Motion Using Directional Motion Estimation
Particle Filter
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Target Tracking Techniques, Particle Filter Techniques (H4)
Parzen
* Fisher, Parzen, and Other Clustering Measures and Decompositions (H2)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Path Planning
* Active Vision - Path/Trajectory Planning (H2)
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* ALV, Autonomous Vehicles, Systems or Vehicles (H2)
* Carnegie Mellon NAVLAB, AMBLER, etc. (H3)
* CMU Road Followers -- ALVINN YARF MANIAC (H3)
* Obstacles, Collision, Other Vehicles, Objects on the Road (H3)
* Planning Robot (Manipulator) Positions (H
* Planning Vehicle Position or Path Planning (H3)
* Road, Path Following Operators, Obstacles (H2)
* Vehicle Control -- Dickmanns (H3)
10 for Path Planning
Pattern Alignment
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Empirical Evaluation of Two Criteria for Pattern Comparison and Alignment
Pattern Classification
* OCR, Document Analysis and Character Recognition Systems (H)
* Optimum Character Recognition System Using Decision Function, An
Pattern Recognition
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Books, Collections, Overviews, General, and Surveys (H)
* Clustering for Region Segmentation (H2)
* Feature Selection in Pattern Recognition or Clustering (H2)
* K-Means Clustering (H2)
* King Sun Fu Pattern Recognition Papers (H2)
* Nearest Neighbor Classification (H2)
* Pattern Recognition Issues (H1)
* Pattern Recognition Systems (H2)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Pattern Recognition, General and Survey Articles (H2)
* Pattern Recognition, General Issues (H2)
* 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
19 for Pattern Recognition
PCA
* Computation and Analysis of Principal Components, Eigen Values, SVD (H3)
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* ICA, PCA in Face Recognition (H4)
* Invariants -- Principal Component Analysis (H3)
* Learning for Principal Components, Eigen Representations (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* 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
10 for PCA
PCB Inspection
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Inspection -- Chips, Wafers, PCB, PWB, IC, Disks, etc. (H3)
PDE
* Books, Collections, Overviews, General, and Surveys (H)
* Mathematical Problems in Image Processing Partial Differential Equations and the Calculus of Variations
Perceptrons
* 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
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Contour Completion, Subjective Contours (H3)
* Detection and Analysis of Edges, Lines, Curves, Corners, Hough Transform (H)
* Grouping, Figure-Ground, Background, Foreground (H2)
* Grouping, Lines and Curves (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Perceptual Grouping, General Systems (H2)
* Perceptual Grouping, Perceptual Organization Techniques (H1)
* Perceptual Grouping, Theory (H2)
* 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?
32 for Perceptual Grouping
Perceptual Organization
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Perceptual Grouping, Theory (H2)
Performance Analysis
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Detection and Analysis of Edges, Lines, Curves, Corners, Hough Transform (H)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* OCR, Document Analysis and Character Recognition Systems (H)
* 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
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Books, Collections, Overviews, General, and Surveys (H)
* Performance Characterization in Computer Vision (H3)
* Performance Issues (H2)
* Performance Characterization in Image Analysis: Thinning, a Case in Point
Perimeter
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Computing Area, Diameter and Perimeter (H3)
Periodic Textures
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Texture Periods Description (H2)
Perspective, Camera Calibration
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Camera Calibration -- Perspective Based, Vanishing Points (H2)
PET
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Positron Emission Tomography -- PET (H2)
Phase-Based
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Modeling Foreshortening in Stereo Vision using Local Spatial Frequency
Phase Correlation
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Empirical Evaluation of Two Criteria for Pattern Comparison and Alignment
Phase Differences
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Fast Computation of Disparity from Phase Differences, The
Phoenix
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Phoenix Image Segmentation System: Description and Evaluation, The
* Recursive Region Segmentation by Analysis of Histograms
Photobook
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Photobook: Tools for Content-Based Manipulation of Image Databases
Photogrammetry
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Filters, Image Processing, Restoration, Enhancement, Image and Video Coding (H)
* Photogrammetry Books (H2)
* Comparison of Two Image Compression Techniques for Softcopy Photogrammetry, A
Photometric Stereo
* 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Albedo, Reflectance Map from Multiple Images (H2)
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Interreflections (H2)
* Light Source Detection (H2)
* Shape from Multiple Light Sources, Photometric Stereo (H1)
* Appearance Characterization of Linear Lambertian Objects, Generalized Photometric Stereo, and Illumination-Invariant Face Recognition
7 for Photometric Stereo
Photometric Stereo, Four Lights
* 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
Photometric Stereo, Reflectance Map
* 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Albedo, Reflectance Map from Multiple Images (H2)
Physics Based Vision
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Deformable Solids -- Pentland Papers (H2)
* Deformable Solids -- Terzopoulos Papers (H2)
* 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
* Detection and Analysis of Edges, Lines, Curves, Corners, Hough Transform (H)
* Piece-Wise Linear Representations from Curves (H3)
Pipeline Processors
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Pipelined Processors and Algorithms (H2)
Planar Motion.
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Understanding Object Motion
Planning
* Active Vision - Path/Trajectory Planning (H2)
* Active Vision -- Visual Attention (H2)
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Camera Position, Sensor Position for Model Generation (H3)
* Planning Optimal Sensor Positions (H4)
* Planning Robot (Manipulator) Positions (H
* Planning Sensor Position, View Selection, View Planning (H3)
* Planning Vehicle Position or Path Planning (H3)
* Visibility Analysis (H3)
9 for Planning
Point Correspondences
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Randomized Polygon Search for Planar Motion Detection
Point Matching
* 2-D Points with 2-D Structures, Point Matching (H2)
* 2-D Points with 3-D Structures (H2)
* 3-D Points with 3-D Structures (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Visually Estimating Workpiece Pose in a Robot Hand Using the Feature Points Method
Polar Representation
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Versatile Machine Vision System for Complex Industrial Parts, A
Polarization
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Polarization Effects (H2)
* Polarization/Radiometric Based Material Classification
* Shape from Polarization Images
Polarized Light
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Target Detection in Optically Scattering Media by Polarization-Difference Imaging
Polygon Matching
* 2-D Region or Contour Matching (H2)
* Partial Contour Matching, Piecewise Segments (H3)
* Piecewise Segment Matching of Contours (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Polygon
* Detection and Analysis of Edges, Lines, Curves, Corners, Hough Transform (H)
* General Polygonal Representations and Computations (H3)
Polygonal Approximation
* Detection and Analysis of Edges, Lines, Curves, Corners, Hough Transform (H)
* OCR, Document Analysis and Character Recognition Systems (H)
* Polygonal Representations from Curves (H3)
* Computer Recognition of Handwritten Numerals by Polygonal Approximations
Polygonal Decomposition
* Detection and Analysis of Edges, Lines, Curves, Corners, Hough Transform (H)
* Polygonal Decomposition Techniques (H4)
Polygonal Description
* Detection and Analysis of Edges, Lines, Curves, Corners, Hough Transform (H)
* Polygonal Representations from Curves (H3)
Polygonal Patches
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Polygonal Surface Patch Models (H3)
Pose Estimation
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* 3-D Object Recognition from Pose Estimation or Alignment (H2)
* 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Grimson Object Recognition Papers (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (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
18 for Pose Estimation
Pose Estimation, Accumulation
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Pose Estimation, 3D Models (H3)
Pose Estimation, Evaluation
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* 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
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Pose Estimation, 3D Models (H3)
Pose Estimation, Lines
* Line Based Matching for Pose Estimation (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Pose Estimation, Perspective
* Line Based Matching for Pose Estimation (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Pose Estimation, Points
* Point Based Pose Estimation and Recognition (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Pose Estimation, Range Data
* Pose Estimation -- Range Data (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Pose, Head
* 3-D Model Based Head Motion, Head Tracking (H2)
* Face Pose, Head Pose (H2)
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Postal Codes
* Numbers, Digits, Zip (Postal) Codes (H
* OCR, Document Analysis and Character Recognition Systems (H)
Posture
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Human Posture, or Human Pose, Human Body Pose (H2)
Primal Sketch
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 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
Principal Components
* Computation and Analysis of Principal Components, Eigen Values, SVD (H3)
* Fisher, Parzen, and Other Clustering Measures and Decompositions (H2)
* ICA, PCA in Face Recognition (H4)
* Invariants -- Principal Component Analysis (H3)
* Learning for Principal Components, Eigen Representations (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Surveys, Comparisons, Evaluations, Principal Components (H3)
8 for Principal Components
Printed Characters
* Handwritten Characters (H3)
* OCR, Document Analysis and Character Recognition Systems (H)
Probabilistic Causal Model
* 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
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Data-driven Procedure for Density-Estimation with Some Applications, A
Probability
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Evidence Theory, Combination Techniques, Optimization Techniques (H3)
* Fuzzy Sets, Fuzzy Logic (H4)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* 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
Progressive Transmission
* Filters, Image Processing, Restoration, Enhancement, Image and Video Coding (H)
* Hierarchical, Multi-Level, Pyramidal Coding Techniques (H2)
Projective Analysis
* 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Shape and Structure from Perspective Effects, Vanishing Points (H1)
Projector
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Projector-Camera Systems, Projection onto Surface (H3)
Protein
* Extraction and Analysis of Proteins (H2)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Proximity Matrix
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Modal Approach to Feature-Based Correspondence
* Modal Matching for Correspondence and Recognition
Psychophysical Evidence
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Defect Detection in Random Color Textures
Pyramid Structure
* 2-D Object Recognition Using Hierarchical Boundary Segments
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Detection and Analysis of Edges, Lines, Curves, Corners, Hough Transform (H)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Multi-level Segmentation and Smoothing Methods (H2)
* Pyramid Representations (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* 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
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Pyramidal Algorithms for Iconic Indexing
Pyramid Technique
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Coarse-Fine Bimodality Analysis of Circular Histogram
Pyramid, Laplacian
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Laplacian Pyramid as a Compact Image Code, The
Pyramids
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Books, Collections, Overviews, General, and Surveys (H)
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Detection and Analysis of Edges, Lines, Curves, Corners, Hough Transform (H)
* Filters, Image Processing, Restoration, Enhancement, Image and Video Coding (H)
* Hierarchical, Multi-Level, Pyramidal Coding Techniques (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* 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