Machined Surfaces
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Statistical-Methods to Compare the Texture Features of Machined Surfaces
Magnetic Resonance
* Functional Magnetic Resonance, fMRI (H3)
* Medical Applications -- Magnetic Resonance, MRI (H1)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* MRI, Noise and Artifact Reduction (H2)
* MRI, Surveys, Overviews, Evaluations (H2)
* Segmentation, Features, Models from Magnetic Resonance Data, MRI (H2)
Mahalanobis Distance
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* On the Generalized Distance in Statistics
* Practical Reliable Bayesian Recognition of 2D and 3D Objects Using Implicit Polynomials and Algebraic Invariants
Mammograms
* Breast Cancer, Mammograms, Analysis, Mammography (H2)
* Mammograms, Image Enhancement (H3)
* Mammograms, Three Dimensional Analysis, Registration (H3)
* Mammograms, Ultrasound (H3)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Manipulator Path Planning
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Planning Robot (Manipulator) Positions (H
Map Recognition
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Fuzzy Pyramid Scheme for Distorted Object Recognition
Maps
* Analysis of Maps (H3)
* OCR, Document Analysis and Character Recognition Systems (H)
MAPS/SPAM
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* CMU MAPS Image Database System (H1)
Markov Chain
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Markov Chain Monte Carlo in Practice
Markov Model
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Rotation and gray scale transform invariant texture identification using wavelet decomposition and hidden Markov model
Markov Random Field
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Markov Random Field Models (H2)
* MRF Models for Segmentation (H2)
* Markov Random-Field Models for Unsupervised Segmentation of Textured Color Images
Massive Parallel
* Array Processors, Massive Parallel Systems, Pyramids (H2)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
MAT
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Processing of Skeletons (H2)
* Skeletons and Axial Descriptions - Medial Axis Transform (MAT) etc. (H
* Skeletons in Three Dimensions (H2)
* Shock Grammar for Recognition, A
* TID: A Translation Invariant Data Structure for Storing Images
7 for MAT
MAT, Three Dimensional
* 3D Medial Surfaces and 3D Skeletons
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Central Axis Algorithm for 3D Bronchial Tree Structures, A
Matched Filter
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Translation-Invariant Optical-Pattern Recognition without Correlation
Matching Pursuits
* Filters, Image Processing, Restoration, Enhancement, Image and Video Coding (H)
* Matching Pursuits, Video Coding (H2)
Matching, 3-D General
* General References (H1)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Matching, 3-D
* 3-D Object Recognition from Pose Estimation or Alignment (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching, Volumes, 3-D (H1)
* Example of 3-D Interpretation of Images Using Bayesian Networks, An
Matching, Accumulation
* 2-D/2-D Lines Accumuation Techniques (H3)
* 2-D/3-D Lines Accumuation Techniques (H3)
* 3-D/3-D Matching Accumulation Techniques (H3)
* Clustering and Accumulation Array Techniques (H3)
* Grimson Object Recognition Papers (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching Using Accumulation and Alignment Schemes (H2)
* Pose Estimation, 3D Models (H3)
* Range Data Matching -- Accumulation Methods (H3)
* Region/Contour Matching, Accumulation Based (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
11 for Matching, Accumulation
Matching, Alignment
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Alignment of Objects with Smooth Surfaces, The
* Online Fingerprint Verification
Matching, Areas
* Optical Flow -- Matching Using Areas (H2)
* Optical Flow Field Computations and Use (H)
Matching, Aspect Graphs
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Aspect Graph Matching -- Bowyer (H3)
* Aspect Graph Matching -- Ikeuchi (H3)
* Aspect Graph Matching, Characteristic Views (H2)
* Aspect Graphs, Matching Systems (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Qualitative 3-D Shape Reconstruction Using Distributed Aspect Graph Matching
7 for Matching, Aspect Graphs
Matching, Boltzmann
* Boltzmann Machine, Simulated Annealing, and Related Topics (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Matching, Boundaries
* Stereo Analysis - Boundaries of Curved Surfaces (H2)
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Matching, Chamfer
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Chamfering: A fast method for obtaining approximations of the Euclidean distance in N dimensions
* Parametric Correspondence and Chamfer Matching: Two New Techniques for Image Matching
* Research in Interactive Scene Analysis
* Scene-Analysis Approach to Remote Sensing, A
Matching, Clustering
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Pattern Recognition, General Issues (H2)
Matching, Combinations
* Combined Feature Matching (H1)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Matching, Constraints
* Constraint Based Matching (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Matching, Context
* Context in Computer Vision (H2)
* Context Supplied by Text or Language (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Matching, Contours
* 2-D Contour Matching, Indexing or Hashing Techniques (H3)
* 2-D Region or Contour Matching (H2)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Contours Through a Sequence (H3)
* Hierarchical/Scale-Space Contour Matching and Descriptions (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching Fourier Descriptors, Fourier Shape Descriptors (H3)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Partial Contour Matching, Piecewise Segments (H3)
* Piecewise Segment Matching of Contours (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Model Based Vision System to Identify and Locate Partially Visible Industrial Parts, A
* On Recognizing and Positioning Curved 3-D Objects from Image Contours
* Shape Matching Using Relaxation Techniques
* Three Dimensional Movement Analysis of Dynamic Line Images
* Wavelet-Based Affine Invariant Representation: A Tool for Recognizing Planar Objects in 3D Space
16 for Matching, Contours
Matching, Correlation
* Correlation Based and Signal Matching Techniques (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Matching, Edges
* 2-D Points with 2-D Structures, Point Matching (H2)
* Edge Based Stereo Analysis: Scan Line Oriented (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Depth from Edge and Intensity Based Stereo
* Fast Stereovision Matcher Based on Prediction and Recursive Verification of Hypothesis, A
* Segment-Based Stereo Matching
* Stereo by Two-Level Dynamic Programming
* Two-View Matching
10 for Matching, Edges
Matching, Eigen Values
* Invariants -- Eigen Representations, General Appearance Based Methods (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Eigen Decomposition Approach to Weighted Graph Matching Problems, An
Matching, Evaluation
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Benchmark Evaluation of a Model-Based Object Recognition System
* Cost of Choosing the Wrong Model in Object Recognition by Constrained Search, The
* Performance Comparison of Scene Matching Techniques
* Performance Evaluation of Shape Matching via Chord Length Distribution
* Recovering 3D Information from Complex Aerial Imagery
8 for Matching, Evaluation
Matching, Features
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Other Feature Matching Techniques (H1)
Matching, Fourier
* Matching Fourier Descriptors, Fourier Shape Descriptors (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Matching, Function
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Recognition by Function (H2)
Matching, Graphs
* Basic Comparison of Relational Network Descriptions (H2)
* Continuous Relaxation Theory (H3)
* General Structure and Graph Representation and Matching (H2)
* Graph Matching and Relaxation (H1)
* Graph Matching Theoretical Issues (H2)
* Graph Matching, Continuous Relaxation (H2)
* Graph Matching, Neural Networks, Hopfield Networks (H2)
* Hummel and Zucker Relaxation Papers (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching Graphs and 3-D Network Descriptions (H2)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Shmuel Peleg Theoretical Relaxation Papers (H3)
* Framework for Estimation of Motion Parameters from Range Images, A
* Some Techniques for Recognizing Structures in Pictures
14 for Matching, Graphs
Matching, Hashing
* 2-D Contour Matching, Indexing or Hashing Techniques (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Three-Dimensional Matching Using Hashing/Indexing (H2)
* Geometric Hashing: A General and Efficient Model-Based Recognition Scheme
* On the Sensitivity of Geometric Hashing
Matching, Hierarchical
* Hierarchical/Scale-Space Contour Matching and Descriptions (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Matching, Hopfield Networks
* Graph Matching, Neural Networks, Hopfield Networks (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Matching, Hough
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching Using Accumulation and Alignment Schemes (H2)
Matching, Images
* Image Registration Techniques (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Matching, Indexing
* 2-D Images of 3-D Oriented Points
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Three-Dimensional Matching Using Hashing/Indexing (H2)
* Efficient Model Library Access by Projectively Invariant Indexing Functions
* Generalized Shape Autocorrelation
* Graycode Representation and Indexing: Efficient Two Dimensional Object Recognition
* Model-Group Indexing for Recognition
8 for Matching, Indexing
Matching, Invariants
* 3-D Object Recognition Using Invariants (H2)
* Invariance Papers -- Mundy (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Principal Component Decompositions, Point features (H2)
* Region or Contour Invariants, Signatures, Metrics for Matching (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Three-Dimensional Matching Using Hashing/Indexing (H2)
* Recognizing 3D Objects Using Photometric Invariant
* Shape Recognition under Affine Distortions
9 for Matching, Invariants
Matching, Lines
* 2-D Lines with 2-D Structure (H2)
* 2-D Lines with 3-D Structure (H2)
* 2-D/2-D Lines Accumuation Techniques (H3)
* 2-D/3-D Lines Accumuation Techniques (H3)
* 3-D Lines with 3-D Structure (H2)
* 3-D/3-D Matching Accumulation Techniques (H3)
* Invariants, Lines, Curves (H3)
* Line Based Matching for Pose Estimation (H2)
* Line Segment Based Stereo Analysis (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching Linear Features (H1)
* Partial Contour Matching, Piecewise Segments (H3)
* Piecewise Segment Matching of Contours (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Locating Structures in Aerial Images
* Matching Linear Features of Images and Maps
* Matching of Natural Terrain Scenes
18 for Matching, Lines
Matching, Models
* 2-D Lines with 3-D Structure (H2)
* 3-D Lines with 3-D Structure (H2)
* 3-D Object Recognition from Pose Estimation or Alignment (H2)
* ACRONYM and SUCCESSOR Papers - Stanford University and Others (H2)
* Constraint Based Matching (H2)
* General Issues -- Knowledge-Based Vision (H2)
* Grimson Object Recognition Papers (H3)
* Knowledge-Based Vision (H1)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching Graphs and 3-D Network Descriptions (H2)
* Model Based Recognition Systems (H2)
* Recognition by Function (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* University of Massachusetts VISIONS System (H2)
* Model-Based Recognition in Robot Vision
15 for Matching, Models
Matching, Moments
* Matching, Descriptions Using Moments (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Aircraft Identification by Moment Invariants
Matching, Networks
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching Graphs and 3-D Network Descriptions (H2)
Matching, Optical Flow
* Optical Flow Field Computation and Analysis (H1)
* Optical Flow Field Computations and Use (H)
Matching, Points
* 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)
* Clustering and Accumulation Array Techniques (H3)
* Invariants, Points (H3)
* Long Sequences, Motion (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Optical Flow Field Computations and Use (H)
* Point Based Pose Estimation and Recognition (H3)
* Point Matching for Optical Flow Computation (H2)
* Point Matching (H1)
* Point Pattern Invariants (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Relaxation Based Techniques (H3)
* Stereo Analysis: Point Matching (H2)
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Automatic Feature Point Extraction and Tracking in Image Sequences for Unknown Camera Motion
* Disparity Analysis of Images
19 for Matching, Points
Matching, Pose
* 3-D Object Recognition from Pose Estimation or Alignment (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Pose Estimation, 3D Models (H3)
Matching, Range Data
* Pose Estimation -- Range Data (H3)
* Range Data Matching -- Accumulation Methods (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Surfaces and Range Data Matching (H2)
Matching, Recognition
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Object Recognition, General Techniques (H1)
Matching, Regions
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 2-D Region or Contour Matching (H2)
* Affine Invariants (H3)
* Invariants -- Eigen Representations, General Appearance Based Methods (H2)
* Invariants, Areas (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching, Affine Transformations (H3)
* Matching, Areas, Regions, Surfaces (H1)
* Region or Contour Invariants, Signatures, Metrics for Matching (H3)
* Region/Contour Matching, Accumulation Based (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Fuzzy Relaxation Approach for Inexact Scene Matching
* Matching of Featured Objects Using Relational Tables from Stereo Images
* Robust matching of 3D contours using iterative closest point algorithm improved by M-estimation
* Semantic Description of Aerial Images Using Stochastic Labeling
* Symbolic Image Registration and Change Detection
* Two-View Matching
17 for Matching, Regions
Matching, Relaxation
* Continuous Relaxation Theory (H3)
* Discrete Relaxation Methods (H2)
* Discrete Relaxation Theoretical Issues (H3)
* Faugeras and Berthod Gradient Optimization Methods (H3)
* Graph Matching, Continuous Relaxation (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Relaxation Based Techniques (H3)
8 for Matching, Relaxation
Matching, Scale-Space
* Hierarchical/Scale-Space Contour Matching and Descriptions (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Matching, Sequence
* Contours Through a Sequence (H3)
* Long Sequence Matching and Motion (H2)
* Long Sequences, Motion (H3)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Using Motion from Orthographic Projections to Prune 3-D Point Matches
Matching, Signature
* Region or Contour Invariants, Signatures, Metrics for Matching (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Matching, Stereo
* Stereo Analysis: Point Matching (H2)
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Matching, Structures
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Other Structural Matching (H2)
Matching, Surfaces
* 3-D Surface Registration for Mosaics and Models (H4)
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Image to 3-D Surface Matching (H4)
* Register 3-D Surfaces, Range Registration (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Surface Matching, Deformable Surface Matching (H2)
* Surfaces and Range Data Matching (H2)
* Automatic 3D to 2D Registration for the Photorealistic Rendering of Urban Scenes
* Constraint-Based Sensor Planning for Scene Modeling
* Navigation Using Image Sequence Analysis and 3-D Terrain Matching
11 for Matching, Surfaces
Matching, Survey
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Relational Matching
* Some Computational Strategies for Object Recognition
Matching, Templates
* Deformable Template Matching (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Template Matching Techniques (H2)
Matching, Textures
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Object Detection Based on Gray Level Cooccurrence
Matching, Theory
* Evidence Theory, Combination Techniques, Optimization Techniques (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Matching, Tree Search
* 3D-POLY: A Robot Vision System for Recognizing Objects in Occluded Environments
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching Using Tree Searching Techniques (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Relational Descriptions in Picture Processing
Matching, Video
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Video Registration Techniques, Synchronizing, Synchronization (H3)
Matching, Volumes
* 3-D Object Recognition Using Invariants (H2)
* Aspect Graph Matching -- Bowyer (H3)
* Aspect Graph Matching -- Ikeuchi (H3)
* Aspect Graph Matching, Characteristic Views (H2)
* Aspect Graphs, Matching Systems (H3)
* Grimson Object Recognition Papers (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching Graphs and 3-D Network Descriptions (H2)
* Matching Using Accumulation and Alignment Schemes (H2)
* Matching, Volumes, 3-D (H1)
* Pose Estimation, 3D Models (H3)
* Three-Dimensional Matching Using Hashing/Indexing (H2)
12 for Matching, Volumes
Mathematical Morphology
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Periodic Lines: Definition, Cascades, and Application to Granulometries
Maximum Likelihood
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Maximum Likelihood Estimation, Classification (H3)
MCMC
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Markov Chain Monte Carlo in Practice
MDL
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* MDL, Minimum Description Length for Shape Measure (H4)
* Segmenting Images Corrupted By Correlated Noise
Measurement
* Automated Measurement Systems (H2)
* Books, Collections, Overviews, General, and Surveys (H)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Reliability Analysis of Parameter Estimation in Linear Models with Applications to Mensuration Problems in Computer Vision
Medial Axis Transform
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Skeletons and Axial Descriptions - Medial Axis Transform (MAT) etc. (H
* Medial Axis Transform-Based Features and a Neural-Network for Human-Chromosome Classification
* Multiscale Medial Axis and Its Applications in Image Registration, The
* Transform for Multiscale Image Segmentation by Integrated Edge and Region Detection, A
* Transformation for Extracting New Descriptions of Shape, A
9 for Medial Axis Transform
Medial Axis
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Generalized Cylinders, Medial Axis Descriptions (H1)
Median Filters
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Median Filtering (H2)
Medical
* Fusion of Medical Data (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Medical, Applications
* Breast Cancer, Mammograms, Analysis, Mammography (H2)
* General Medical Applications (H1)
* Lungs, and Lung Cancer Image Analysis (H2)
* Mammograms, Image Enhancement (H3)
* Mammograms, Three Dimensional Analysis, Registration (H3)
* Mammograms, Ultrasound (H3)
* Medical Applications -- Cancer Diagnosis (H1)
* Medical Applications -- Endoscopy, Colonscopy (H1)
* Medical Applications -- General Systems (H1)
* Medical Applications -- Surgery (H1)
* Medical Applications -- Surveys (H1)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Pulmonary Nodules (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Retinal Images, Analysis of Eye, etc. (H1)
* Ribs, Chest X-Rays (H3)
* Automatic MR-PET Registration Algorithm
* Robust Hierarchical Algorithm for Constructing a Mosaic from Images of the Curved Human Retina
19 for Medical, Applications
Mensuration
* Automated Measurement Systems (H2)
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Close Range Photogrammetry: Principles, Techniques and Applications
Mesh Models
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Triangulated Surface Models, Mesh Models (H3)
Metrology
* Automated Measurement Systems (H2)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Microcalcification
* Breast Cancer, Mammograms, Analysis, Mammography (H2)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Microwave
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Microwave Sensors and Analysis (H2)
Minimal Spanning Tree
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Decision Trees (H2)
* Detection and Analysis of Edges, Lines, Curves, Corners, Hough Transform (H)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Curvilinear Feature Extraction Using Minimum Spanning Trees
* Data-driven Procedure for Density-Estimation with Some Applications, A
* Minimal Spanning Tree-Based Clustering Technique: Relationship with Bayes Classifier
* Parallel Algorithm For Constructing Minimum Spanning Trees, A
8 for Minimal Spanning Tree
Minimum Description Length
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* MDL, Minimum Description Length for Shape Measure (H4)
* Region Competition and its Analysis: A Unified Theory for Image Segmentation
Minutiae
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Fingerprint Features, Minutiae, Ridges (H2)
* Fingerprint Features, Ridges, Flow, Orientation Based (H3)
Mixed Pixels
* Mixed Pixels, Subpixel Classification (H3)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Mixture Models
* Mixture Models, Mixed Pixels (H2)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Mobile Robots
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Autonomous Vehicles (H1)
* Vision for Mobile Robot Navigation: A Survey
Model-Based Descriptions
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Parameterized Models, Fit Model to Objects (H3)
Model Acquisition
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Learning Object Models from Appearance
Model Based Recognition
* 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 Object Recognition Using Invariants (H2)
* ACRONYM and SUCCESSOR Papers - Stanford University and Others (H2)
* ACRONYM and SUCCESSOR Papers - Stanford University and Others (H2)
* Aspect Graph Matching, Characteristic Views (H2)
* ATR -- Model, Object Based Radar and SAR Recognition (H3)
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Constraint Based Matching (H2)
* Context in Computer Vision (H2)
* Knowledge-Based Vision (H1)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Model Based Recognition Systems (H2)
* Recognition by Function (H2)
* Three-Dimensional Matching Using Hashing/Indexing (H2)
* University of Massachusetts VISIONS System (H2)
* University of Massachusetts VISIONS System (H2)
* Constructing Constraint Tables for Model-Based Recognition and Localization
* Region-Oriented Image-Analysis System by Computer, A
19 for Model Based Recognition
Model Based Segmentation
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Fua and Leclerc Guided Segmentation Papers (H2)
* Techniques for Model Guided Segmentation (H1)
Model Based Vision
* Learning Model Descriptions (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Model-Based Recognition in Robot Vision
* Survey of Model-Based Image Analysis Systems
Model Based
* Books, Collections, Overviews, General, and Surveys (H)
* Expert Vision Systems (H3)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Model-Based Image Analysis of Human Motion Using Constraint Propagation
Moire
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Real-time Optically Processed Face Recognition System Based on Arbitrary Moire Contours
Moment Invariants
* Matching, Descriptions Using Moments (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Moments
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Matching, Descriptions Using Moments (H3)
* Moment Computation, Computation of Moments (H4)
* OCR, Document Analysis and Character Recognition Systems (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Extending The Feature Vector For Automatic Face Recognition
* Method of Normalization to Determine Invariants, The
* Object Recognition by Three Dimensional Moment Invariants
* Optical Character Recognition by the Method of Moments
* Orientation of 3-D Structures in Medical Images
* Orthogonal Moment Features for Use with Parametric and Nonparametric Classifiers
* Review of Algorithms for Shape Analysis, A
* Shape Analysis of Three Dimensional Objects Using Range Information
15 for Moments
Moments, Computation
* Moment Computation, Computation of Moments (H4)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Moments, Three-Dimensional
* 3-D Moment Forms: Their Construction and Application to Object Identification and Positioning
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Montage
* Image Montage, Mosaic Generation, Super Resolution and Stabilization (H1)
* Mosaic Generation for Video (H3)
* Mosaic Generation (H2)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Morphology
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Morphology - General, Surveys (H2)
* Morphology - Techniques and Applications (H2)
* Morphology - Theory (H2)
* Morphology (H1)
* Automatic generation of image-segmentation processes
* Automatic Screening of Cytological Specimens
* Geodesic Saliency of Watershed Contours and Hierarchical Segmentation
* Morpholog: A Software Package for the Quantitative Image Analysis
* Spectral and Rank Order Approaches to Texture Analysis
14 for Morphology
Morphology, Implementations
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Morphological Operator Decomposition (H3)
MOSAIC System
* 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* MOSAIC System -- Herman (H2)
Mosaic
* Document Mosaic Generation (H3)
* Image Montage, Mosaic Generation, Super Resolution and Stabilization (H1)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Mosaic Generation for Video (H3)
* Mosaic Generation (H2)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Panoramic Image Creation (H3)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Retinal Mosaic Generation (H3)
* Building mosaics from video using MPEG motion vectors
* Detecting and Tracking Moving Objects in Video from an Airborne Observer
* Feature-Based, Robust, Hierarchical Algorithm for Registering Pairs of Images of the Curved Human Retina, A
* Independent Motion: The Importance of History
* Iso-Shaping Rigid Bodies for Estimating Their Motion From Image Sequences
* Robust Parameter Estimation in Computer Vision
17 for Mosaic
Mosaicking
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Electronic Digital Stabilization: Design and Evaluation, with Applications
Motion Analysis
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Video Database Indexing, Motion Analysis (H4)
Motion and Depth
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Motion Using Depth Information (H2)
* Motion Using Stereo Pairs or Depth -- Features (H1)
* Motion with Optical Flow and Depth (H2)
Motion and Stereo
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Motion Using Stereo Pairs or Depth -- Features (H1)
* Motion Using Stereo Pairs or Depth (H1)
* Integrated Stereo-Based Approach to Automatic Vehicle Guidance, An
Motion Compensation
* Computation for General Motion Compensation, Motion Estimation (H4)
* Filters, Image Processing, Restoration, Enhancement, Image and Video Coding (H)
* Global Motion Compensation (H4)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Motion Compensation for Coding (H4)
* New Merit Version for MPEG-2 Encoded Files, A
* Two-Stage Motion Compensation Using Adaptive Global MC and Local Affine MC
7 for Motion Compensation
Motion Segmentation
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Expectation-Maximisation Framework for Segmentation and Grouping, An
Motion Tracking
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Target Tracking Systems (H3)
Motion
* Arm Tracking for Gestures (H4)
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Hand Tracking for Gestures (H3)
Motion, Coding
* Computation for Vector Fields, Flow Fields (H4)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Filters, Image Processing, Restoration, Enhancement, Image and Video Coding (H)
* Moving Image Coding, Compression: Using Vector Fields, Flow Fields (H4)
* Wavelets for Image Coding -- Quantization Issues (H4)
* Wavelets for Image Coding (H3)
* Wavelets for Motion and Video Coding (H3)
* Motion-Compensated Television Coding: Some new Results
8 for Motion, Coding
Motion, Compression
* Filters, Image Processing, Restoration, Enhancement, Image and Video Coding (H)
* Moving Image Coding, Compression: Using Vector Fields, Flow Fields (H4)
Motion, Detection
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Background Detection, Background Model (H3)
* Consecutive Image Differencing Techniques (H2)
* Differencing Papers -- Ramesh Jain (H3)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Motion Detection, Analysis of Motion Detectors (H2)
* Motion Sequence, Background Subtraction (H4)
* Moving Object Extraction, Using Models or Analysis of Regions (H3)
* Shadows and Motion, Detection and Extraction (H3)
* Surveillance Applications, Motion Detection (H1)
* Unified Approach to Moving Object Detection in 2D and 3D Scenes, A
12 for Motion, Detection
Motion, Differencing
* Consecutive Image Differencing Techniques (H2)
* Differencing Papers -- Ramesh Jain (H3)
* Image Differencing, Motion Segmentation and Filtering Techniques (H1)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Formation of an Object Concept by Analysis of Systematic Time Variations in the Optically Perceptible Environment
Motion, Discontinuity
* Image Segmentation from Motion Information (H2)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Motion Edges -- Detection and Analysis (H1)
* Optical Flow Field -- Boundaries (H2)
* Optical Flow Field -- Multiple Flows, Transparent Layers, Motion Layers (H2)
* Optical Flow Field Computations and Use (H)
* Simple Scheme for Motion Boundary Detection, A
7 for Motion, Discontinuity
Motion, Edges
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Motion Edges -- Detection and Analysis (H1)
Motion, Epipolar plane
* Epipolar-Plane Analysis in Spatio-Temporal Analysis (H2)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Motion, Estimation Equations
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Equation Estimation Methods (H1)
Motion, Estimation Evaluation
* Error Analysis of Motion and Structure Computations (H2)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Error Analysis of Motion Parameter Estimation from Image Sequences
* Performance Bounds for Estimating Three-Dimensional Motion Parameters from a Sequence of Noisy Images
* Recovering 3-D Motion Parameters from Image Sequences with Gross Errors
* Robust Algorithms for Motion Estimation Based on Two Sequential Stereo Image Pairs
* Some Properties of the E Matrix in Two-View Motion Estimation
8 for Motion, Estimation Evaluation
Motion, Estimation
* 3-D Kalman Filter for Image Motion Estimation
* Filters, Image Processing, Restoration, Enhancement, Image and Video Coding (H)
Motion, Factorization
* Factorization Approach to Motion (H2)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Shape and Motion from Image Streams: A Factorization Method
Motion, Feature Based
* General Feature Based Motion (H1)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Motion, Five Frames
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Estimates Using 5 or More Frames (H2)
* Shariat and Related Papers (H3)
Motion, FOE
* Focus of Expansion and Other Features (H2)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Optical Flow Field Computations and Use (H)
* Determining Motion Parameters for Scenes with Translation and Rotation
* Estimating 3-D Egomotion from Perspective Image Sequences
Motion, Four Frames
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Estimates Using 4 Frames (H2)
Motion, Hardware
* 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Depth And Motion Analysis Machine, The
Motion, Human
* Human Motion, General Analysis (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Tracking Animals, Animal Gait (H4)
* Tracking People with 3D Models (H4)
* Tracking People with Multiple Cameras or Depth (H4)
* Factorization-Based Approach for Articulated Nonrigid Shape, Motion and Kinematic Chain Recovery From Video, A
* Human and Object Tracking and Verification in Video
9 for Motion, Human
Motion, Kalman filter
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Estimation of Object Motion Parameters from Noisy Images
Motion, Lines
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Estimation of Displacements from Two 3-D Frames Obtained from Stereo
Motion, Low Level
* Low Level Motion, General Issues (H1)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Motion, Many Frames
* Broida and Related Work (H3)
* Integration over a Sequence (H2)
* Long Sequence Matching and Motion (H2)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Motion Estimates Using 5 or More Frames (H2)
* Optical Flow Field Computations and Use (H)
* Spatio-Temporal Analysis -- Many Frames (H1)
* Robust Estimation of Multiple Motions: Affine and Piecewise-Smooth Flow-Fields, The
9 for Motion, Many Frames
Motion, Matching
* Long Sequences, Motion (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Motion, Multiple frames
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Euclidean Reconstruction: From Paraperspective to Perspective
Motion, Multiple
* Image Segmentation from Motion Information (H2)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Optical Flow Field -- Boundaries (H2)
* Optical Flow Field -- Multiple Flows, Transparent Layers, Motion Layers (H2)
* Optical Flow Field Computations and Use (H)
Motion, Nonrigid
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Nonrigid, Deformable Motion Analysis and Tracking (H2)
Motion, Observer
* Egomotion or Ego Motion Computation from Flow Fields (H2)
* More Direct Ego Motion Computation (H3)
* Optical Flow Field Computations and Use (H)
Motion, Optical Flow
* Optical Flow Field Computation -- General Issues (H1)
* Optical Flow Field Computations and Use (H)
Motion, Parameters
* Egomotion or Ego Motion Computation from Flow Fields (H2)
* More Direct Ego Motion Computation (H3)
* Optical Flow Field Computations and Use (H)
Motion, Planning
* Active Vision - Path/Trajectory Planning (H2)
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Planning Robot (Manipulator) Positions (H
* Planning Sensor Position, View Selection, View Planning (H3)
* Planning Vehicle Position or Path Planning (H3)
Motion, Psychology
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Psychology and Psychophysics (H1)
Motion, Psychophysics
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Psychology and Psychophysics (H1)
Motion, Regions
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Segmentation, Matching and Estimation of Structure and Motion of Textured Piecewise Planar Surfaces
Motion, Rigidity Constraint
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Determining the Movement of Objects from a Sequence of Images
* Uniqueness and Estimation of 3-D Motion Parameters and Surface Structures of Rigid Objects
Motion, Rotation
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Optical Flow Field Computations and Use (H)
* Rotation Only (H2)
* Special Case Motion Estimation (H1)
* Analyzing Orthographic Projection of Multiple 3-D Velocity Vector Fields in Optical Flow
* Self-Calibration from Multiple Views with a Rotating Camera
7 for Motion, Rotation
Motion, Segmentation
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Extract Moving Objects from Sequences (H2)
* Image Segmentation from Motion Information (H2)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Motion Segmentation, Object Extraction in Compressed Domains (H3)
* Optical Flow Field -- Boundaries (H2)
* Optical Flow Field -- Multiple Flows, Transparent Layers, Motion Layers (H2)
* Optical Flow Field Computations and Use (H)
* Shadows and Motion, Detection and Extraction (H3)
* Velocity Determination in Scenes Containing Several Moving Objects
10 for Motion, Segmentation
Motion, Smoothness Constraint
* Optical Flow Field -- Smoothness (H1)
* Optical Flow Field Computations and Use (H)
Motion, Spatio-Temporal
* General Spatio-Temporal Analysis (H2)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Spatio-Temporal Analysis -- Many Frames (H1)
Motion, Structure Evaluation
* Error Analysis of Motion and Structure Computations (H2)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Accuracy of 3D Parameters in Correspondence-Based Techniques, The
* Perception of Structure from Motion: I: Optic Flow vs. Discrete Displacements; II: Lower Bound Results
* Refinement of Environmental Depth Maps over Multiple Frames
Motion, Structure
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Structure from Motion - Other (H1)
* Structure, Depth, and Shape from Motion (H1)
* Acceleration-Based Structure-from-Motion
* Analysis of Long Image Sequence for Structure and Motion Estimation
* Empirical Study of Structure from Motion, The
* Epipolar-Plane Image Analysis: An Approach to Determining Structure from Motion
* Estimating Motion and Structure from Line Matches: Performance Obtained and Beyond
* Interpretation of Structure from Motion, The
* Kinematics of a Rigid Object from a Sequence of Noisy Images: A Batch Approach
* Maximizing Rigidity: The Incremental Recovery of 3-D Structure from Rigidity and Rubbery Motion
* Motion and Structure from Motion from Point and Line Matches
* Natural Representation of Motion in Space-Time
* Observing Jointed Objects
* On Combining Points and Lines in an Image Sequence to Recover 3D Structure and Motion
* On Kineopsis and Computation of Structure and Motion
* Polynomial Methods for Structure from Motion
* Representation and Tracking of Point Structures Using Stereovision
* Simple Procedure to Solve Motion and Structure from Three Orthographic Views, A
20 for Motion, Structure
Motion, Surface Reconstruction
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Optical Flow Field Computations and Use (H)
* Surface or Contour Motion Using Global Surfaces (H1)
* Surface Reconstruction from Optical Flow (H1)
Motion, Survey
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Optical Flow Field Computations and Use (H)
* Analysis of Visual Motion by Biological and Computer Systems
* Analysis Techniques for Image Sequences
* Computational Analysis of Time-Varying Images, A
* Computing Motion and Structure from Noisy, Time-Varying Image Velocity Information
* Derivation of Optical Flow Using a Spatiotemporal-Frequency Approach
* Dynamic Scene Analysis
* Estimation of Motion from a Pair of Range Images: A Review
* Motion and Structure from Feature Correspondences: A Review
* Motion Segmentation and Estimation by Constraint Line Filtering
* On the Computation of Motion from Sequences of Images: A Review
13 for Motion, Survey
Motion, Three Frames
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Motion Estimates Using 3 Frames (H2)
* Affine Structure from Line Correspondences with Uncalibrated Affine Cameras
* Computing Two Motions from Three Frames
Motion, Tracking
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Long Sequence Matching and Motion (H2)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Estimates Using 5 or More Frames (H2)
* Region, Target Tracking (H2)
* Snakes, Motion Tracking (H2)
* Tracking of Moving Objects and Matching in Sequences (H1)
* Computer Analysis of Moving Polygonal Images
8 for Motion, Tracking
Motion, Translation
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Optical Flow Field Computations and Use (H)
* Optical Flow for Simple Motions (H2)
* Special Case Motion Estimation (H1)
* Translation Only (H2)
Motion, Two Frames
* Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Estimates Using 2 Frames (H2)
* Univ. of Illinois Parameter Estimation Papers (H3)
* Relative Orientation
Motion, Walking
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Motion Analysis of Human Ambulatory Patterns
Moving Light Displays
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Lights: A Study in Motion
* Observing Jointed Objects
* Recognition of Moving Light Displays Using Hidden Markov-Models
* Tracking Three Dimensional Moving Light Displays
MPEG Standard
* Filters, Image Processing, Restoration, Enhancement, Image and Video Coding (H)
* MPEG: A Video Compression Standard for Multimedia Applications
MPEG
* Filters, Image Processing, Restoration, Enhancement, Image and Video Coding (H)
* MPEG 4 Issues (H3)
* MPEG 7 Issues (H3)
* MPEG and Related Standard Coding Methods (H2)
* MPEG Error Concealment Issues (H3)
* MPEG Hardware and Implementations (H3)
* MPEG Rate-Distortion Trade-Offs, Transmissions Issues (H3)
* MPEG Standard (H3)
8 for MPEG
MRF
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Markov Random Field Models (H2)
MRI
* Brain, Cortex, MRI Analysis, Models, 3-D (H2)
* Brain, Cortex, MRI Segmentation (H3)
* Brain, Cortex, Registration, MRI, Other (H3)
* Heart, Cardiac, Angiography using MRI Analysis (H2)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Multi-Grid
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Reconstruction, Hierarchical, Multi-Grid Approaches (H2)
Multi-level Segmentation
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Multi-level Segmentation and Smoothing Methods (H2)
Multi-Scale computations
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Scale Space Computation of Features (H2)
Multi-Scale
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Multi-Scale, Pyramid Texture Segmentation Approaches (H2)
* Optical Flow Field Computations and Use (H)
* Scale Space and Multi-Scale Techniques (H1)
* Fast Scalable Algorithm for Discontinuous Optical-Flow Estimation, A
Multilevel Reconstruction
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Volumetric Segmentation Using Hierarchical Representation And Triangulated Surface
Multimedia
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Multimedia, Audio-Visual Communications, Survey (H2)
* Multimedia, Augmented Reality, Virtual Reality, Applications (H1)
* OCR, Document Analysis and Character Recognition Systems (H)
* Watermarks in Video and Multi-Media, Other Data (H2)
Multiple Light Sources
* 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Shape from Multiple Light Sources, Photometric Stereo (H1)
Multiple Motions
* Image Segmentation from Motion Information (H2)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Optical Flow Field -- Boundaries (H2)
* Optical Flow Field -- Multiple Flows, Transparent Layers, Motion Layers (H2)
* Optical Flow Field Computations and Use (H)
* Closing the Loop on Multiple Motions
Multiple Resolutions
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Detection and Analysis of Edges, Lines, Curves, Corners, Hough Transform (H)
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Multiple Resolution Edge Detectors to Improve Performance, Hierarchical (H2)
* Optical Flow -- Hierarchical, Multi-Grid, Multi-Scale Approaches (H2)
* Optical Flow Field Computations and Use (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Stereo Systems: Multiple Resolutions, Hierarchical (H2)
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Edge Detection by Computer Using Planning
* Fast Algorithms for Estimating Local Image Properties
* Layered Recognition Cone Networks That Preprocess Classify and Describe
* Multiple Resolution Representation and Probabilistic Matching of 2-D Gray-Scale Shape
* Multiple Resolution Skeletons
* VISIONS: A computer System for Interpreting Scenes
* Visual Identification of People by Computer
18 for Multiple Resolutions
Multiple Sensors
* Shape Computations from Multiple Sensors (H1)
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Multiple Thresholds
* 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Segmentation by Thresholding, Quantization, or Relaxation (H2)
Multiple Views
* 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* MOSAIC System -- Herman (H2)
* Three-Dimensional Reconstruction from Different Views (H1)
Multiple Views, Stereo
* Multiple Cameras or Views, Multi-Baseline (H1)
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Multiresolution
* Filters, Image Processing, Restoration, Enhancement, Image and Video Coding (H)
* Multiresolution, Hierarchical Restoration Techniques (H3)
Multiscale Representation
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Towards Effective Planar Shape Representation with Multiscale Digital Curvature Analysis Based on Signal-processing Techniques
Multiscale
* 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Hierarchical, Multi-Scale Texture Representations and Analysis (H2)
Multispectral
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Designing a Deer Detection System Using a Multistage Classification Approach
Multiview Geometry
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Multiview Geometry: Profiles and Self-Calibration
Music
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Music Related Gestures Systems (H3)
* Music (H2)
* New Unsorted Entries, and Other Miscellaneous Papers (H)
Musical Notation
* Analysis of Music, Musical Notation (H3)
* OCR, Document Analysis and Character Recognition Systems (H)