Readings in Computer Vision

Issues, Problem, Principles, and Paradigms

1st Edition - June 1, 1987
Editors: Martin A. Fischler, Oscar Firschein
Language: English
Paperback ISBN:
9 7 8 - 0 - 9 3 4 6 1 3 - 3 3 - 0
eBook ISBN:
9 7 8 - 0 - 0 8 - 0 5 1 5 8 1 - 6

The field of computer vision combines techniques from physics, mathematics, psychology, artificial intelligence, and computer science to examine how machines might construct me… Read more

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The field of computer vision combines techniques from physics, mathematics, psychology, artificial intelligence, and computer science to examine how machines might construct meaningful descriptions of their surrounding environment. The editors of this volume, prominent researchers and leaders of the SRI International AI Center Perception Group, have selected sixty papers, most published since 1980, with the viewpoint that computer vision is concerned with solving seven basic problems:

Reconstructing 3D scenes from 2D images
Decomposing images into their component parts
Recognizing and assigning labels to scene objects
Deducing and describing relations among scene objects
Determining the nature of computer architectures that can support the visual function
Representing abstractions in the world of computer memory
Matching stored descriptions to image representation

Each chapter of this volume addresses one of these problems through an introductory discussion, which identifies major ideas and summarizes approaches, and through reprints of key research papers. Two appendices on crucial assumptions in image interpretation and on parallel architectures for vision applications, a glossary of technical terms, and a comprehensive bibliography and index complete the volume.

Readings in Computer Vision: Issues, Problems, Principles, and ParadigmsEdited by Martin A. Fischler and Oscar Firschein

CHAPTER 1: RECOVERING SCENE GEOMETRY

A Stochastic Approach to Stereo Vision, S.Barnard Epipolar-Plane Image Analysis: A Technique for Analyzing Motion Sequences, R.Bolles & H.Baker Preface--The Changing Shape of Computer Vision, M.Brady Understanding Image Intensities, B.Horn A Computer Algorithm for Reconstructing a Scene from Two Projections, H.Longuet-Higgins Practical Real-Time Imaging Stereo Matcher, H.Nishihara Detection of Binocular Disparities, K.Prazdny Hierarchical Warp Stereo, L.Quam Stereo Integral Equation, G.Smith Recovering the Camera Parameters from a Transformation Matrix, T.Strat One-Eyed Stereo: A General Approach to Modeling 3-D Scene Geometry, T.Strat and M.Fischler An Algebraic Approach to Shape-fromImage Problems, K.Sugihara Analysis of Visual Motion by Biological and Computer Systems, S.Ullman An Image Flow Paradigm, A.M.Waxman

CHAPTER 2: IMAGE PARTITIONING AND PERCEPTUAL ORGANIZATION

Extracting Straight Lines, J.Burns, A.Hanson, & E.Riseman A Computational Approach to Edge Detection, J.Canny Linear Delineation, M.Fischler & H.Wolf Perceptual Organization and Curve Partitioning, M.Fischler & R.Bolles Digital Stereo Edges from Zero Crossing of Second Directional Derivatives, R.Haralick Parts of Recognition, D.Hoffman & W.Richards Textons, The Fundamental Elements in Preattentive Vision and Perception of Textures, B.Julesz & J.Bergen Mapping Image Properties into Shape Constraints: Skewed Symmetry, Affine-Transformable Patterns, and the Shape-from-Texture Paradigm, T.Kanade & J.Kender Analyzing Oriented Patterns, M.Kass & A.Witkin Capturing the Local Structure of Image Discontinuities in Two Dimensions, Y.Leclerc Segmentation and Aggregation: An Approach to Figure-Ground Phenomena, D.Lowe & T.Binford Color Constancy: A Method for Recovering Surface Spectral Reflectance, L.Maloney & B.Wandell Visual Routines, S.Ullman Scale-Space Filtering, A.Witkin Early Orientation Selection: Tangent Fields and the Dimensionality of Their Support, S.Zucker

CHAPTER 3: RECOGNITION AND LABELING OF SCENE OBJECTS

3DPO: A Three-Dimensional Part Orientation System, R.Bolles, P.Howard, & M.Hannah Model-Based Three-Dimensional Interpretations of TwoDimensional Images, R.Brooks Special Purpose Automatic Programming for 3D Model-Based Vision, Chris Goad Model-Based Recognition and Localization from Sparse Range or Tactile Data, W.Eric, L.Grimson, & T.Lozano-Perez Rule-Based Interpretation of Aerial Imagery, D.McKeown,Jr., W.Harvey,Jr., & J.McDermott

CHAPTER 4: RELATIONAL DESCRIPTION

Visual Map Making for a Mobile Robot, R.Brooks A Heuristic Program to Solve Geometric-Analogy Problems, T.Evans Problem-Solving with Diagrammatic Representations, B.Funt The 3D MOSAIC Scene Understanding System: Incremental Reconstruction of 3D Scenes for Complex Images, M.Herman & T.Kanade Terrain Models for an Autonomous Land Vehicle, D.Lawton, T.Levitt, C.McConnell, & J.Glicksman Experiments in Using a Theorem Prover to Prove and Develop Geometrical Theorems in Computer Vision, M.Swain & J.Mundy Knowledge Organization and Its Role in Representation and Interpretation for Time-Varying Data: The ALVEN System, J.Tsotsos

CHAPTER 5: VISION SYSTEM ARCHITECTURES AND COMPUTATIONAL PARADIGMS

A Learning Algorithm for Boltzmann Machines, D.Ackley, G.Hinton, & T.Sejnowski Parameter Nets, D.Ballard Image Processing by Simulated Annealing, P.Carnevali, L.Coletti, & S.Patarnello Preface to S.Geman and D.Geman, "Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images," G.Smith Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images, S.Geman & D.Geman On the Foundations of Relaxation Labeling Processes, R.Hummel & S.Zucker Optimization by Simulated Annealing, S.Kirkpatrick, C.Gelatt,Jr., & M.Vecchi Visual Information Processing: Artificial Intelligence and the Sensorium of Sight, D.Marr & H.Nishihara Computational Vision and Regularization Theory, T.Poggio, V.Torre, & C.Koch

CHAPTER 6: REPRESENTATIONS AND TRANSFORMATIONS

Geometry for Construction and Display, D.Ahuja & S.Coons Global and Local Deformations of Solid Primitives, A.Barr The Laplacian Pyramid as a Compact Image Code, P.Burt & E.Adelson Perceptual Organization and the Representation of Natural Form, A.Pentland Codon Constraints on Closed 2D Shapes, W.Richards & D.Hoffman

CHAPTER 7: MATCHING, MODEL FITTING, DEDUCTION, AND INFORMATION INTEGRATION

Generalizing the Hough Transform to Detect Arbitrary Shapes, D.Ballard Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography, M.Fischler & R.Bolles Detection of Roads and Linear Structures in Low-Resolution Aerial Imagery Using a Multisource Knowledge Integration Technique, M.Fischler, J.Tenenbaum, & H.Wolf Representations Based on Zero-crossings in Scale-Space, R.Hummel Signal Matching Through Scale Space, A.Witkin, D.Terzopoulis, & M.Kass

APPENDIX A: KEY IDEAS, ASSUMPTIONS, AND OPEN ISSUES IN COMPUTER VISION

APPENDIX B: PARALLEL COMPUTER ARCHITECTURES FOR COMPUTER VISION

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Readings in Computer Vision

Issues, Problem, Principles, and Paradigms

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