Beck / Hope / Rosenfeld Human and Machine Vision

1. Auflage 2014
ISBN: 978-1-4832-6696-1
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 580 Seiten, Web PDF

Human and Machine Vision provides information pertinent to an interdisciplinary program of research in visual perception. This book presents a psychophysical study of the human visual system, which provides insights on how to model the flexibility required by a general-purpose visual system. Organized into 17 chapters, this book begins with an overview of how a visual display is segmented into components on the basis of textual differences. This text then proposes three criteria for judging representations of shape. Other chapters consider an increased use of machine vision programs as models of human vision and of data from human vision in developing programs for machine vision. This book discusses as well the diversity and flexibility of systems for representing visual information. The final chapter deals with dot patterns and discusses the process of interring orientation information from collections of them. This book is a valuable resource for psychologists, neurophysiologists, and computer scientists.

Autoren/Hrsg.

Beck, Jacob

Hope, Barbara

Rosenfeld, Azriel

Inhaltsverzeichnis

1;Front Cover;1
2;Human and Machine Vision;4
3;Copyright Page;5
4;Table of Contents;6
5;Contributors;8
6;Preface;10
7;Acknowledgments;12
8;Chapter 1. A Theory of Textural Segmentation;14
8.1;Abstract;14
8.2;1. Introduction;14
8.3;2. Properties Producing Textural Segmentation;18
8.4;3. Linking Operations;23
8.5;4. Second-order Statistics;40
8.6;5. Model for Textural Segmentation;44
8.7;6. Julesz's Dipole Model;48
8.8;Acknowledgment;49
8.9;References;50
9;Chapter 2. Criteria for Representations of Shape;52
9.1;Abstract;52
9.2;1. Introduction;52
9.3;2. An Illustration: Generalized Cones;54
9.4;3. Two-dimensional Shape Description: Smoothed Local Symmetries;59
9.5;4. Three-dimensional Surfaces: Curvature Patches;79
9.6;Acknowledgment;93
9.7;References;93
10;Chapter 3. Contrasts between Human and Machine
Vision: Should Technology Recapitulate Phylogeny?;98
10.1;Abstract;98
10.2;1. The Primacy of Depth Perception;100
10.3;2. Perception and Contradictory Knowledge;101
10.4;3. Heuristic Processes in Perception;102
10.5;4. Ecological Optics;104
10.6;5. Conclusion;106
10.7;Acknowledgment;107
10.8;References;107
11;Chapter 4. Flexibility in Representational Systems;110
11.1;Abstract;110
11.2;References;118
12;Chapter 5. Computing with Connections;120
12.1;Abstract;120
12.2;1. Introduction;120
12.3;2. Neuron-like Computing Units;127
12.4;3. Networks of Units;135
12.5;4. Conserving Connections;147
12.6;5. Applications;153
12.7;6. Conclusions;163
12.8;Acknowledgment;164
12.9;Appendix;164
12.10;References;165
13;Chapter 6. Stimulus Information and Processing Mechanisms in Visual Space Perception;170
13.1;Abstract;170
13.2;1. Introduction;171
13.3;2. Stimulus Analysis of Space in Scenes;175
13.4;3. A Stimulus Analysis of Pictures;185
13.5;4. The Stimulus Information in Motion Pictures;190
13.6;5. Processing of Stimulus Information about the Layout of Space;193
13.7;6. Information Processing of Pictures;219
13.8;7. The Processing of Motion Pictures;234
13.9;8. Conclusion;239
13.10;References;240
14;Chapter 7. Mapping Image Properties into Shape Constraints: Skewed Symmetry, Affine-Transformable Patterns, and the
Shape-from-Texture Paradigm;250
14.1;Abstract;250
14.2;1. Introduction;250
14.3;2. Skewed Symmetry;251
14.4;3. Affine-Transformable Patterns;253
14.5;4. The Shape-from-texture Paradigm;259
14.6;5. Applications of Skewed Symmetry and Affine-transformable Patterns;263
14.7;6. Conclusion;267
14.8;Acknowledgment;268
14.9;Appendix;269
14.10;References;270
15;Chapter 8. Visual Computation;272
15.1;Abstract;272
15.2;1. Stability and Motion;273
15.3;2. Control;273
15.4;3. Shape and Color;274
15.5;4. Elements and Skills;276
15.6;5. People and Machines;279
15.7;Acknowledgment;280
15.8;References;280
16;Chapter 9. The Psychology of Perceptual Organization: A
Transformational Approach;282
16.1;Abstract;282
16.2;1. Introduction;282
16.3;2. Transformations, Group Structure, and Invariance;284
16.4;3. Phenomena of Perceptual Organization;286
16.5;4. Toward a Theory of Perceptual Organization;319
16.6;5. Organizational Phenomena Revisited;343
16.7;6. Conclusion;346
16.8;Acknowledgment;347
16.9;References;348
17;Chapter 10. Why the Human Perceiver Is a Bad Machine;354
17.1;Abstract;354
17.2;1. Constraint Handling;355
17.3;2. Some Lapses of Precision;356
17.4;3. Some Lapses of Control;362
17.5;4. Human Talents;365
17.6;5. The Human Style and the Machine Style;371
17.7;Acknowledgment;373
17.8;References;374
18;Chapter 11. Spatiotemporal Interpolation in Vision;378
18.1;Abstract;378
18.2;Part I;379
18.2.1;1. Introduction;379
18.2.2;2. Methods;380
18.3;Part II;388
18.3.1;1. Spatiotemporal Interpolation: How Is It Done?;388
18.3.2;2. Interpolation Schemes;392
18.3.3;3. Discussion;397
18.3.4;4. Conclusions;401
18.4;Appendix;404
18.5;References;405
19;Chapter 12. Isolating Representational Systems;408
19.1;Abstract;408
19.2;1. Visual Pattern Recognition;412
19.3;2. Imagery;416
19.4;3. Cross-modality Processing;419
19.5;4. Conclusions;421
19.6;Acknowledgment;422
19.7;References;422
20;Chapter 13. A Sketch of a (Computational) Theory of
Visual Kinesthesis;426
20.1;Abstract;426
20.2;References;435
21;Chapter 14. Environment-Centered Representation of Spatial Layout: Available Visual Information
from Texture and Perspective;438
21.1;Abstract;438
21.2;1. Introduction;438
21.3;2. Texture;442
21.4;3. Perspective;448
21.5;4. Finding the Perspective Structure;456
21.6;5. The Terrestrial Horizon;462
21.7;6. Conclusion;468
21.8;Acknowledgment;469
21.9;References;469
22;Chapter 15. Recent Computational Studies in the Interpretation
of Structure from Motion;472
22.1;Abstract;472
22.2;1. Introduction;472
22.3;2. The Rigidity-based Interpretation of Structure from Motion;474
22.4;3. Alternative Schemes and Additional Results;475
22.5;4. Remarks Concerning the Different Schemes and their Relevance to Perception;480
22.6;5. Concluding Remarks;487
22.7;Acknowledgment;488
22.8;Appendix;488
22.9;References;491
23;Chapter 16. On the Role of Structure in Vision;494
23.1;Abstract;494
23.2;1. Introduction;494
23.3;2. Background;496
23.4;3. The Role of Structure;508
23.5;4. Implications for Computational Vision;524
23.6;5. Summary and Conclusions;549
23.7;Acknowledgment;552
23.8;References;552
24;Chapter 17. Computational and Psychophysical Experimentsin Grouping: Early Orientation Selection;558
24.1;Abstract;558
24.2;1. Introduction;558
24.3;2. On the Role of Early Grouping Processes;560
24.4;3. Size and Density Constraints for Very Early Grouping Processes;561
24.5;4. Type I and Type II Processes;562
24.6;5. A Model for Orientation Selection;571
24.7;6. Experiments with the Model;574
24.8;7. Consequences, Implications, and Speculations;575
24.9;8. Summary and Conclusions;578
24.10;Acknowledgment;578
24.11;References;579