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Proceedings Paper

Methods for combination of evidence in function-based 3D object recognition
Author(s): Louise Stark; Lawrence O. Hall; Kevin W. Bowyer
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Paper Abstract

A system which utilizes a function-based representation has been implemented and tested, using the object category `chair' for a case study. Functional description is used to recognize classes and identify subclasses of known categories of objects, even if the specific object has never been encountered previously. Interpretation of the functionality of an object is accomplished through qualitative reasoning about its 3-D shape. During the recognition process, evidence is gathered as to how well the functional requirements are met by the input shape. An investigation of different types of operators used in the combination of the functional evidence has been made. Three pairs of conjunctive and disjunctive operators have been used in the recognition process of the 100+ object shapes. The results are compared and differences are discussed.

Paper Details

Date Published: 16 December 1992
PDF: 14 pages
Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); doi: 10.1117/12.130813
Show Author Affiliations
Louise Stark, Univ. of South Florida (United States)
Lawrence O. Hall, Univ. of South Florida (United States)
Kevin W. Bowyer, Univ. of South Florida (United States)

Published in SPIE Proceedings Vol. 1766:
Neural and Stochastic Methods in Image and Signal Processing
Su-Shing Chen, Editor(s)

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