Overview

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 large numbers of relatively straightforward image processing routines is used to recognize natural features such as trees, bushes, and rocks. The use of contextual information is the key to simplifying the problem to the extent that well understood algorithms give reliable results in ground-level, outdoor scenes.

Full Product Details

Author:   Thomas M. Strat
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Dimensions:   Width: 15.50cm , Height: 1.10cm , Length: 23.50cm
Weight:   0.308kg
ISBN:  

9781461277255

ISBN 10:   1461277256
Pages:   173
Publication Date:   20 October 2013
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

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.

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