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Proceedings Paper

Multiresolution motion estimation and target detection
Author(s): Robert E. Karlsen; David J. Gorsich; Grant R. Gerhart
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Paper Abstract

Detecting and characterizing motion in a scene can play a critical role in target detection algorithms, since many targets can be camouflaged so completely that, if they are not moving, they are nearly undetectable. However, once they begin moving, they `popout' and are immediately detected. Estimating motion is also important in human vision modeling, because motion is generally detected with peripheral vision, which can cover the field of regard much more quickly than foveal vision. In this paper, we present two hierarchical multiresolution methods for computing the optical flow in a scene. We use statistical properties of the resulting flow fields to compute a motion feature vector, which we relate to the conspicuity of the moving target in a scene via a neural network.

Paper Details

Date Published: 7 July 1998
PDF: 6 pages
Proc. SPIE 3375, Targets and Backgrounds: Characterization and Representation IV, (7 July 1998); doi: 10.1117/12.327150
Show Author Affiliations
Robert E. Karlsen, U.S. Army Tank-Automotive and Armaments Command (United States)
David J. Gorsich, U.S. Army Tank-Automotive and Armaments Command (United States)
Grant R. Gerhart, U.S. Army Tank-Automotive and Armaments Command (United States)


Published in SPIE Proceedings Vol. 3375:
Targets and Backgrounds: Characterization and Representation IV
Wendell R. Watkins; Dieter Clement, Editor(s)

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