Vector quantization enhancement for computer vision tasks

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Abstract

This paper augments the Bag-of-Word scheme in several respects: we incorporate a category label into the clustering process, build classifier-tailored codebooks, and weight codewords according to their probability to occur. A size-adaptive feature clustering algorithm is also proposed as an alternative to k-means. Experiments on the PASCAL VOC 2007 challenge validate the approach for classical hard-assignment as well as VLAD encoding.

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APA

Trichet, R., & O’Connor, N. E. (2016). Vector quantization enhancement for computer vision tasks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10016 LNCS, pp. 398–409). Springer Verlag. https://doi.org/10.1007/978-3-319-48680-2_35

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