Model-based fusion of FLIR, color, and ladar

J. Ross Beveridge; Allen R. Hanson; Durga P. Panda

doi:10.1117/12.220945

15 September 1995 Model-based fusion of FLIR, color, and ladar

J. Ross Beveridge, Allen R. Hanson, Durga P. Panda

Proceedings Volume 2589, Sensor Fusion and Networked Robotics VIII; (1995) https://doi.org/10.1117/12.220945
Event: Photonics East '95, 1995, Philadelphia, PA, United States

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.

Citation Download Citation

J. Ross Beveridge, Allen R. Hanson, and Durga P. Panda "Model-based fusion of FLIR, color, and ladar", Proc. SPIE 2589, Sensor Fusion and Networked Robotics VIII, (15 September 1995); https://doi.org/10.1117/12.220945

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