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Effective image parsing needs a representation that is both selective (to inter-class variations) and invariant (to intra-class variations). CodeBook from bag-of-visual-words representation addresses the invariance, and part-based models can potentially address the selectivity. However, existing part-based approaches either require expensive manual object-level labeling or make strong assumptions...
Recently, a new clustering method called maximum margin clustering (MMC) was proposed and has shown promising performances. It was originally formulated as a difficult nonconvex integer problem. To make the MMC problem practical, the researchers either relaxed the original MMC problem to inefficient convex optimization problems or reformulated it to nonconvex optimization problems, which sacrifice...
This paper addresses the problem of video scene classification based on the small amount of natural language description created for the video stream. The approach incorporates a conventional tf·idf term-document matrix with scene class specific information derived using the maximum a posteriori (MAP) estimates and the chi-square statistic. Further latent semantic analysis (LSA) is applied to find...
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