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Proceedings Paper

Angle- and distance-constrained matcher with parallel implementations for model-based vision
Author(s): David J. Anhalt; Steven Raney; William E. Severson
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Paper Abstract

The matching component of a model-based vision system hypothesizes one-to-one correspondences between 2D image features and locations on the 3D model. As part of Wright Laboratory's ARAGTAP program [a synthetic aperture radar (SAR) object recognition program], we developed a matcher that searches for feature matches based on the hypothesized object type and aspect angle. Search is constrained by the presumed accuracy of the hypothesized aspect angle and scale. These constraints reduce the search space for matches, thus improving match performance and quality. The algorithm is presented and compared with a matcher based on geometric hashing. Parallel implementations on commercially available shared memory MIMD machines, distributed memory MIMD machines, and SIMD machines are presented and contrasted.

Paper Details

Date Published: 1 February 1992
PDF: 13 pages
Proc. SPIE 1609, Model-Based Vision Development and Tools, (1 February 1992); doi: 10.1117/12.57113
Show Author Affiliations
David J. Anhalt, Martin Marietta Corp. (United States)
Steven Raney, Martin Marietta Corp. (United States)
William E. Severson, Martin Marietta Corp. (United States)

Published in SPIE Proceedings Vol. 1609:
Model-Based Vision Development and Tools
Rodney M. Larson; Hatem N. Nasr, Editor(s)

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