3D target recognition using quasi-optimal visual filters
Barnabás Takács, Lev S. Sadovnik · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
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.