Abstract
The Bag-of-Words (BoW) derived from local keypoints was widely applied in visual information research such as image search, video retrieval, object categorization, and computer vision. Construction of visual codebook is a well-known and predominant method for the representation of BoW. However, a visual codebook usually has a high dimension that results in high computational complexity. In this paper, an approach is presented for constructing a compact visual codebook. Two important parameters, namely the likelihood ratio and the significant level, are proposed to estimate the discriminative capability of each of the codewords. Thus, the codewords that have higher discriminative capability are reserved, and the others are removed. Experiments prove that application of the proposed compact codebook not only reduces computational complexity, but also improves performance of object classification..
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Wang, Z., Liu, G., Qian, X., Guo, D. (2010). An Approach to the Compact and Efficient Visual Codebook Based on SIFT Descriptor. In: Qiu, G., Lam, K.M., Kiya, H., Xue, XY., Kuo, CC.J., Lew, M.S. (eds) Advances in Multimedia Information Processing - PCM 2010. PCM 2010. Lecture Notes in Computer Science, vol 6297. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15702-8_42
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DOI: https://doi.org/10.1007/978-3-642-15702-8_42
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