Angle- and distance-constrained matcher with parallel implementations for model-based vision

David J. Anhalt; Steven Raney; William E. Severson

doi:10.1117/12.57113

1 February 1992 Angle- and distance-constrained matcher with parallel implementations for model-based vision

David J. Anhalt, Steven Raney, William E. Severson

Proceedings Volume 1609, Model-Based Vision Development and Tools; (1992) https://doi.org/10.1117/12.57113
Event: Robotics '91, 1991, Boston, MA, United States

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.

Citation Download Citation

David J. Anhalt, Steven Raney, and William E. Severson "Angle- and distance-constrained matcher with parallel implementations for model-based vision", Proc. SPIE 1609, Model-Based Vision Development and Tools, (1 February 1992); https://doi.org/10.1117/12.57113

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