Rosenfeld Human and Machine Vision II

1. Auflage 2014
ISBN: 978-1-4832-7628-1
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 376 Seiten, Web PDF

Perspectives in Computing: Human and Machine Vision II compiles papers presented at the second Workshop on Human and Machine Vision held in Montreal, Canada on August 1-3, 1984. This book discusses the perception of transparency in man and machine, human image understanding, and connectionist models and parallelism in high level vision. The theory of the perceived spatial layout of scenes, generative systems of analyzers, and codon constraints on closed 2D shapes are also elaborated. This text likewise covers the environment- and viewer-centered perception of surface orientation, autonomous scene description with range imagery, and pre-attentive processing in vision. This publication is recommended for students and researchers interested in both fields of visual perception and computer vision.

Autoren/Hrsg.

Rosenfeld, Azriel

Inhaltsverzeichnis

1;Front Cover;1
2;Human and Machine Vision II;4
3;Copyright Page;5
4;Table of Contents;6
5;Preface;8
6;Contributors;10
7;Chapter 1. Perception of Transparency in Man and Machine;12
7.1;1. INTRODUCTION;12
7.2;2. ADDITIVE COLOR MIXTURE;13
7.3;3. SUBTRACTIVE COLOR MIXTURE;15
7.4;4. NONVERIDICAL PERCEPTION OF TRANSPARENCY;17
7.5;5. REFLECTANCE VS LIGHTNESS;18
7.6;6. PERCEPTION OF THE DEGREE OF TRANSPARENCY;19
7.7;7. FIGURAL CUES;21
7.8;8. HUMAN AND MACHINE JUDGMENTS OF TRANSPARENCY;23
7.9;REFERENCES;23
8;Chapter 2. Human Image Understanding: Recent Research and a Theory;24
8.1;RECOGNITION: UNITS AND CATEGORIES;25
8.2;THEORETICAL DOMAIN: PRIMAL ACCESS;26
8.3;BASIC PHENOMENA OF OBJECT RECOGNITION;27
8.4;RECOGNITION-BY-COMPONENTS;27
8.5;A PERCEPTUAL BASIS FOR A COMPONENTIAL REPRESENTATION;30
8.6;COMPONENTS GENERATED FROM DIFFERENCES IN NONACCIDENTAL PROPERTIES AMONG GENERALIZED CONES;33
8.7;RELATIONS OF RBC TO PRINCIPLES OF PERCEPTUAL ORGANIZATION;40
8.8;A LIMITED NUMBER OF COMPONENTS?;40
8.9;EXPERIMENTAL SUPPORT FOR A COMPONENTIAL REPRESENTATION;45
8.10;SUMMARY AND IMPLICATIONS OF THE EXPERIMENTAL RESULTS;60
8.11;CONCLUSION;65
8.12;REFERENCES;65
9;Chapter 3. Describing Surfaces;69
9.1;1. INTRODUCTION;69
9.2;2. SURFACE CURVES;71
9.3;3. COMPUTATIONAL EXPERIMENTS;85
9.4;APPENDIX A;93
9.5;APPENDIX B: THE GENERALIZED CONE THEOREM;93
9.6;ACKNOWLEDGMENTS;94
9.7;REFERENCES;94
10;Chapter 4. Connectionist Models and Parallelism in High Level Vision;97
10.1;1. INTRODUCTION;97
10.2;2. CONNECTIONIST MODELS;100
10.3;3. PARALLEL VISUAL RECOGNITION;107
10.4;4. LIMITS ON PARALLELISM;113
10.5;REFERENCES;117
11;Chapter 5. Toward a Theory of the Perceived Spatial Layout of Scenes;120
11.1;1. INTRODUCTION;120
11.2;2. MEASURING PERCEIVED LAYOUT FROM RESPONSES ABOUT A SCENE;130
11.3;3. EXPERIMENTAL PROCEDURE TO MEASURE PRECEIVED LAYOUT;131
11.4;4. RESULTS OF EMPIRICAL MEASUREMENTS OF PERCEIVED LAYOUT;134
11.5;5. HOW GOOD ARE THESE MEASURES OF PERCEIVED LAYOUT OF SPACE;143
11.6;6. PROPERTIES OF THE PERCEIVED LAYOUT OF SPACE;145
11.7;7. VARIABLES THAT AFFECT THE PERCEIVED LAYOUT OF SPACE;147
11.8;8. THE THEORETICAL IMPORTANCE OF THE STUDY OF PERCEIVED LAYOUT;152
11.9;ACKNOWLEDGMENTS;155
11.10;REFERENCES;155
12;Chapter 6. Generative Systems of Analyzers;160
12.1;1. INTRODUCTION;160
12.2;2. AN EXAMPLE;160
12.3;3. THE GENERATIVE STRUCTURE;167
12.4;4. THE STRUCTURE OF GROUPING;171
12.5;5. WIRING TOGETHER THE EXTERNAL AND INTERNAL ANALYZER SYSTEMS;177
12.6;6. ANALYZER SYSTEMS ENCODING THE CARTESIAN REFERENCE FRAMES;180
12.7;7. THE JOHANSSON MOTION PHENOMENON;190
12.8;8. THE ANALYSIS OF COMPLEX SHAPE;192
12.9;REFERENCES;199
13;Chapter 7. Early Vision: From Computational Structure to Algorithms and Parallel Hardware;201
13.1;1. INTRODUCTION;201
13.2;2. ANALOG NETWORKS FOR SOLVING VARIATIONAL PROBLEMS;208
13.3;3. CONCLUSION;213
13.4;ACKNOWLEDGMENTS;215
13.5;REFERENCES;215
14;Chapter 8. Codon Constraints on Closed 2D Shapes;218
14.1;1. INTRODUCTION;218
14.2;2. THE REPRESENTATION;218
14.3;3. PART DESCRIPTORS: CODONS;219
14.4;4. CONSTRAINTS ON SMOOTH CODON STRINGS;221
14.5;5. CLOSED CODONS;223
14.6;6. MIRROR REVERSAL, HOLES, AND FIGURE-GROUND;224
14.7;7. INDEX DEVELOPMENT;225
14.8;8. MAPPING 3D ~ 2D;226
14.9;9. SUMMARY;228
14.10;APPENDIX I: A BINARY MAPPING FOR CODON STRINGS;228
14.11;APPENDIX II: NUMBERS OF POSSIBLE OPEN, SMOOTH CODON STRINGS;229
14.12;APPENDIX III: NUMBER OF SMOOTH CLOSED CODON STRINGS;231
14.13;ACKNOWLEDGMENTS;234
14.14;REFERENCES;234
15;Chapter 9. Environment-Centered and Viewer-Centered Perception of Surface Orientation;235
15.1;1. INTRODUCTION;235
15.2;2. EXPERIMENT I;237
15.3;3. EXPERIMENT II;242
15.4;4. CONCLUSIONS;245
15.5;ACKNOWLEDGMENTS;246
15.6;REFERENCES;246
16;Chapter 10. Perception of Organization in a Random Stimulus;248
16.1;ACKNOWLEDGEMENT;252
16.2;REFERENCES;253
17;Chapter 11. Autonomous Scene Description with Range Imagery;254
17.1;1. INTRODUCTION;254
17.2;2. TAXONOMY OF CONTOURS IN LIGHT-STRIPE IMAGES;255
17.3;3. CONTOUR ANALYSIS;257
17.4;4. SURFACE ANALYSIS;259
17.5;5. OBJECT ANALYSIS;263
17.6;6. MULTIPLE SCENE ANALYSIS;264
17.7;7. SUMMARY;266
17.8;ACKNOWLEDGMENTS;266
17.9;REFERENCES;266
18;Chapter 12. Intelligible Encoding of ASL Image Sequences at Extremely Low Information Rates;267
18.1;1. INTRODUCTION AND OVERVIEW;267
18.2;2. EARLY STUDIES OF COMPRESSED ASL;270
18.3;3. COMPRESSION TECHNIQUES;274
18.4;4. EXPERIMENT 1. RATINGS OF 81 IMAGE TRANSFORMATIONS;283
18.5;5. EXPERIMENT 2. INTELLIGIBILITY TESTS OF 12 IMAGE TRANSFORMATIONS;287
18.6;6. EXPERIMENT 3. POLYGONAL APPROXIMATIONS;296
18.7;7. COMPRESSED CODES FOR ASL IMAGE SEQUENCES;303
18.8;8. THE TRADEOFFS BETWEEN INTELLIGIBILITY AND BITS PER SECOND;314
18.9;ACKNOWLEDGMENTS;320
18.10;REFERENCES;320
19;Chapter 13. Preattentive Processing in Vision;324
19.1;ACKNOWLEDGMENTS;344
19.2;REFERENCES;344
20;Chapter 14. Early Orientation Selection: Tangent Fields and the Dimensionality of Their Support;346
20.1;1. INTRODUCTION;346
20.2;2. THE FRAMEWORK;348
20.3;3. STATIC AND DYNAMIC FLOWS;350
20.4;4. TANGENTS, VECTOR FIELDS, AND THE RECOVERY OF CONTOURS;350
20.5;5. OUTLINE OF A MODEL FOR ORIENTATION SELECTION;350
20.6;6. DOT PATTERNS AND THE GEOMETRY OF ORIENTATION SELECTION;351
20.7;7. A MODEL FOR EARLY ORIENTATION SELECTION AND GROUPING;352
20.8;8. RESPONSE MATCHING PROBLEMS AND FUNCTIONAL MINIMIZATION;357
20.9;9. RESULTS OF THE ORIENTATION SELECTION ALGORITHM;360
20.10;10. PREDICTIONS;360
20.11;11. FROM CONTOURS TO HAIR PATTERNS;364
20.12;12. TYPE I AND TYPE II PROCESSES;365
20.13;13. ESTIMATING TANGENTS IN TYPE II PATTERNS;366
20.14;14. THE DIFFERENCE BETWEEN TYPE I AND TYPE II PROCESSES;367
20.15;15. PSYCHOPHYSICAL PREDICTIONS FOR TYPE II PATTERNS;369
20.16;16. SIMPLE AND COMPLEX CELLS;370
20.17;17. CONCLUSIONS;373
20.18;ACKNOWLEDGMENTS;374
20.19;REFERENCES;374
21;PERSPECTIVES IN COMPUTING;376