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12 May 2010 Toward a robust 3D-model-based ground target classification system for airborne platforms
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Future target acquisition missions of military aircraft require a robust classification and tracking system of ground targets. In combination with onboard ATD systems, a fast "Find, Fix, Track" cycle for airborne platforms using EO, IR and SAR imaging sensors should be achieved. For EO/IR image sequences, a 3D matching and pose estimation method was developed by EADS internal research. The approach determines the resemblance between rendered 3D CAD models and sensor images to identify the best-matching object pose by optimizing different similarity measures. In order to assess the suitability of this method for real-world military aircraft missions, the present paper introduces a number of robustness requirements w.r.t. sensors, scenarios, object classes and environmental conditions and systematically evaluates the proposed method on a set of image sequences ranging from purely synthetic over laboratory conditions to real-world recordings in a rapid prototyping environment using graphics cards acceleration techniques. The outlook shows possible extensions of the system e.g. tracking and hypothesis management modules as well as the necessary steps to implement and integrate the selected method into a real-time embedded onboard mission system.
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Wolfgang Ensinger, Christoph Stahl, Peter Knappe, Klaus Schertler, and Jörg Liebelt "Toward a robust 3D-model-based ground target classification system for airborne platforms", Proc. SPIE 7696, Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI, 76960L (12 May 2010);

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