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Proceedings Paper

Model-based fusion of FLIR, color, and ladar
Author(s): J. Ross Beveridge; Allen R. Hanson; Durga P. Panda
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Paper Abstract

The complementary nature of LADAR, FLIR and color data for Automatic Target Recognition (ATR) is being explored by new algorithms in a three stage recognition system. The stages are initial detection, target class and pose hypothesis generation, and precise model to multisensor coregistration matching. Coregistration globally aligns 3D target models with range, IR and color imagery while simultaneously refining registration parameters between sensors. This model directed approach is expected to improve ATR performance for occluded targets, targets seen at unusual angles, and targets in cluttered settings. Color is used for initial target detection under daylight conditions. Camouflage learned from training examples generalizes across vehicles and distinguishes targets from natural terrain. Target class and pose hypothesis generation will draw upon existing LADAR boundary matching work extended to tolerate more occlusion, clutter and viewpoint variation. New model to multisensor coregistration algorithms appear robust in early tests and are the basis for future coregistration matching. A new interactive 3D visualization environment allows inspection of multisensor data, coregistration, and monitoring of recognition.

Paper Details

Date Published: 15 September 1995
PDF: 10 pages
Proc. SPIE 2589, Sensor Fusion and Networked Robotics VIII, (15 September 1995); doi: 10.1117/12.220945
Show Author Affiliations
J. Ross Beveridge, Colorado State Univ. (United States)
Allen R. Hanson, Univ. of Massachusetts/Amerst (United States)
Durga P. Panda, Alliant Techsystems Inc. (United States)

Published in SPIE Proceedings Vol. 2589:
Sensor Fusion and Networked Robotics VIII
Paul S. Schenker; Gerard T. McKee, Editor(s)

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