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18 September 1998 3D target recognition using quasi-optimal visual filters
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We describe a general approach for the representation and recognition of 3D objects, as it applies to Automatic Target Recognition (ATR) tasks. The method is based on locally adaptive target segmentation, biologically motivated image processing and a novel view selection mechanism that develops 'visual filters' responsive to specific target classes to encode the complete viewing sphere with a small number of prototypical examples. The optimal set of visual filters is found via a cross-validation-like data reduction algorithm used to train banks of back propagation (BP) neural networks. Experimental results on synthetic and real-world imagery demonstrate the feasibility of our approach.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Barnabas Takacs and Lev S. Sadovnik "3D target recognition using quasi-optimal visual filters", Proc. SPIE 3371, Automatic Target Recognition VIII, (18 September 1998);

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