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Proceedings Paper

Hypothesis Generation In A Theorem Proving Based Recognition System
Author(s): Mitchell Nathan
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Paper Abstract

Two mechanisms are presented which select viable candidates for a pattern matching process. This selection process is termed hypothesis generation. One mechanism is data-driven, using viewpoint dependent features to eliminate obviously poor choices and inhibit unlikely choices. The second mechanism is context-driven, using previously recognized objects as cues for generating future match candidates. These mechanisms have been incorporated into a theorem proving based pattern matching system and serve to constrain the space of possible matches. This isolates the system performance from the effects of the large search space that is necessary for a general-purpose vision system operating in an unconstrained environment.

Paper Details

Date Published: 11 December 1985
PDF: 7 pages
Proc. SPIE 0579, Intelligent Robots and Computer Vision IV, (11 December 1985); doi: 10.1117/12.950798
Show Author Affiliations
Mitchell Nathan, Martin Marietta Aerospace (United States)

Published in SPIE Proceedings Vol. 0579:
Intelligent Robots and Computer Vision IV
David P. Casasent, Editor(s)

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