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- W232414902 abstract "Typically, video copy detection can be done by comparing signatures of new content with of known contents in database. However, this method requires high computation for both database generation and signature detection. In this paper, we proposed an efficient and fast video signature for video copy protection. The video features of a scene are extracted and then transformed to be a signature as a bit-wise string. All string signatures then are stored and manipulated by n-gram based text retrieval algorithm, which is proposed as a replacement with computation-intensive content similarity detection algorithm. The evaluation on the CC_WEB_VIDEO dataset shows that its accuracy is 85% where our baseline algorithms achieved only 75%; however, our algorithm is around 20 times as fast as the baseline." @default.
- W232414902 created "2016-06-24" @default.
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- W232414902 date "2014-01-01" @default.
- W232414902 modified "2023-09-27" @default.
- W232414902 title "N-Gram Signature for Video Copy Detection" @default.
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- W232414902 doi "https://doi.org/10.1007/978-3-319-06538-0_33" @default.
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