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ABSTRACT
Nowadays, the issue of near-duplicate video matching has been extensively studied. However, transformation, which is one of the major causes of near-duplicates, has been little discussed. In this paper, we focus on the fact that a certain kind of feature may per-form excellently to deal with one type of transformation while not be that good on another. We present a self-similarity matrix based near-duplicate video matching scheme with an additional transformation recognition module. By detecting the type of transformations, the near-duplicates can be treated with the 'best' feature which is decided experimentally. Thus, we obtain an enhanced matching result by employing the selected feature. Our work includes seven features and ten transformations respectively, and experimental results show the effectiveness of transformation recognition and the promotion it brings to boost the near-duplicate matching scheme.
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