Perceptual Organization and Visual Recognition
COMPUTER VISION is a field of research that encompasses many objectives. A primary goal has been to construct visual sensors that can provide general-purpose robots with the same information about their surroundings as we receive from our own visual senses. This book takes an important step towards...
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| Format: | eBook |
| Language: | English |
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New York, NY
Springer US
1985, 1985
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| Edition: | 1st ed. 1985 |
| Series: | The Springer International Series in Engineering and Computer Science
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 1. Introduction
- 1.0 Overview of spatial vision
- 1.1 Two viewpoints on computer vision
- 1.2 A demonstration of perceptual organization
- 1.3 Specific functions of perceptual organization
- 2. Previous Research
- 2.1 Gestalt psychology and perceptual organization
- 2.2 The principle of simplicity
- 2.3 Grouping as the formation of causal relations
- 2.4 The role of grouping in computer vision systems
- 3. The Significance of Image Relations
- 3.1 Probability of accidental occurrence
- 3.2 Limiting computational complexity
- 3.3 Conclusions
- 4. The Segmentation of Image Curves
- 4.1 Previous research on curve segmentation
- 4.2 Significance of a curve segmentation
- 4.3 Selecting the most significant structures
- 4.4 Demonstration of the algorithm
- 4.5 Evaluation and future research
- 5. The Use of Viewpoint Invariance
- 5.1 Three-space inferences from image features
- 5.2 Recovery of 3D properties from line drawings
- 5.3 A demonstration of three-space inference
- 5.4 Conclusions and future development
- 6. Model-based Search and Inference
- 6.1 Searching the space of possible viewpoints
- 6.2 Searching the space of possible objects
- 6.3 Summary
- 7. The Verification of Interpretations
- 7.1 Viewpoint determination in human vision
- 7.2 Definition of the problem
- 7.3 Previous research on viewpoint determination
- 7.4 Formulation of perspective projection
- 7.5 Newton-Raphson convergence
- 7.6 Solving for model parameters
- 7.7 Matching lines instead of points
- 7.8 Implementation and future research
- 8. The Scerpo Vision System
- 8.1 Edge detection
- 8.2 Perceptual organization
- 8.3 Matching and evidential reasoning
- 8.4 Verification
- 8.5 System performance and future extensions
- 9. Conclusions
- 9.1 Directions for future development
- Bibliographic Index