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Proceedings Paper

Recognition via alignment using aspect models
Author(s): George C. Stockman; Bruce E. Flinchbaugh
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Paper Abstract

Recognition via alignment is a method for recognizing the general class of rigid objects, which includes vehicles, known terrain, and buildings. A candidate alignment transformation is computed from a minimal set of three corresponding points from model to image, and the transformation and model are accepted only after an expensive verification step. Methods are given here which can dramatically reduce the amount of computation required for recognition by alignment. First, the use of aspects is proposed to cut down on the combinatorics of point correspondence. Secondly, two practical constraints on orientation and size are shown to eliminate many alignment candidates before the expensive verification step. Simulations are reported which show the usefulness of the proposed methods in the context of automatic target recognition.

Paper Details

Date Published: 1 January 1990
PDF: 12 pages
Proc. SPIE 1293, Applications of Artificial Intelligence VIII, (1 January 1990); doi: 10.1117/12.21073
Show Author Affiliations
George C. Stockman, Michigan State Univ. (United States)
Bruce E. Flinchbaugh, Texas Instruments Inc. (United States)


Published in SPIE Proceedings Vol. 1293:
Applications of Artificial Intelligence VIII
Mohan M. Trivedi, Editor(s)

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