Toward A Discriminative Codebook: Codeword Selection across Multi-resolution

In patch-based object recognition, there are two important issues on the codebook generation: (1) resolution: a coarse codebook lacks sufficient discriminative power, and an over-fine one is sensitive to noise; (2) codeword selection: non-discriminative codewords not only increase the codebook size, but also can hurt the recognition performance. To achieve a discriminative codebook for better recognition, this paper argues that these two issues are strongly related and should be solved as a whole. In this paper, a multi-resolution codebook is first designed via hierarchical clustering. With a reasonable size, it includes all of the codewords which cross a large number of resolution levels. More importantly, it forms a diverse candidate codeword set that is critical to codeword selection. A Boosting feature selection approach is modified to select the discriminative codewords from this multi-resolution codebook. By doing so, the obtained codebook is composed of the most discriminative ...

• Type: Conference
• Year: 2007
• Where: CVPR
• Authors: Lei Wang
• Keywords: Coarse Codebook, Codebook Generation, Codebook Size, Computer Vision, CVPR 2007, Discriminative Codebook, Multi-resolution Codebook