Natural Object Recognition
Natural Object Recognition presents a totally new approach to the automation of scene understanding. Rather than attempting to construct highly specialized algorithms for recognizing physical objects, as is customary in modern computer vision research, the application and subsequent evaluation of la...
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| Format: | eBook |
| Language: | English |
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New York, NY
Springer New York
1992, 1992
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| Edition: | 1st ed. 1992 |
| Series: | Springer Series in Perception Engineering
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| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 1 Introduction
- 1.1 Motivation
- 1.2 Issues
- 1.3 Contribution
- 1.4 Example of results
- 2 Natural Object Recognition
- 2.1 Visual capabilities for autonomous robots
- 2.2 Related research
- 2.3 Limitations of current machine-vision technology
- 2.4 Key ideas
- 2.5 Experimental results
- 2.6 Conclusions
- 3 A Vision System for off-Road Navigation
- 3.1 Task scenario
- 3.2 Prior knowledge
- 3.3 The role of geometry
- 3.4 A vocabulary for recognition
- 3.5 Contextual information
- 4 Context-Based Vision
- 4.1 Conceptual Architecture
- 4.2 Implementation of Condor
- 4.3 Example of natural-object recognition
- 4.4 Automated knowledge acquisition
- 4.5 Complexity analysis
- 4.6 Discussion
- 4 Context-Based Vision
- 5.1 Evaluation scenario
- 5.2 Experimentation
- 5.3 Analysis of results
- 6 Conclusion
- 6.1 Contribution
- 6.2 Evaluation
- 6.3 Summary
- A The Core Knowledge Structure
- A.1 Introduction
- A.2 Core Knowledge Structure
- A.3 Logical Interpretation of the CKS Database
- A.3.1 Semantics
- A.3.2 Insertions
- A.3.3 Queries
- A.3.4 User-Defined Relations
- A.3.5 Discussion
- A.4 Slot Access
- A.5 Summary
- References