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Proceedings Paper

Beyond pure static shape in function-based object recognition
Author(s): Kevin W. Bowyer; Louise Stark
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Paper Abstract

There has recently been growing interest in exploiting the concept of reasoning about function for object recognition. In a function-based approach to object recognition, recognition of an object means labeling it as belonging to some category of objects according to the function that it could serve. The few function-based recognition systems which have so far been described in the literature have all assumed that the input to the problem is a pure static shape description. By `pure' shape we mean that the only object property that the systems have reasoned about is their abstract shape. By `static' shape we mean that the systems have reasoned about an object from only a single (assumed rigid) abstract shape instance. This paper discusses some of the issues which must be addressed in extending the function-based approach to handle non-shape properties (such as material properties) and dynamic shape descriptions.

Paper Details

Date Published: 20 August 1993
PDF: 7 pages
Proc. SPIE 2055, Intelligent Robots and Computer Vision XII: Algorithms and Techniques, (20 August 1993); doi: 10.1117/12.150134
Show Author Affiliations
Kevin W. Bowyer, Univ. of South Florida (United States)
Louise Stark, Univ. of the Pacific (United States)


Published in SPIE Proceedings Vol. 2055:
Intelligent Robots and Computer Vision XII: Algorithms and Techniques
David P. Casasent, Editor(s)

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