Biologically Inspired Class-Specific Codebook Construction

Aiming at class-specific recognition tasks, a novel method is presented to improve the object recognition performance of a biologically inspired model by learning class specific feature codebook. The feature codebook is multi-class shared in the original model, and the content proportion for different codeword type is set in uniform distribution.According to corresponding discriminability, we modify the codebook content proportion for different codeword types(feature vector sizes and filter scales). The test results demonstrate that the codebooks built with proposed modification achieve higher total-length efficiency.