Thomas M. Strat

Natural Object Recognition (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 173
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781461229322
• Artikelnr.: 44171354

Inhaltsangabe

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.