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Video Similarity Detection for Digital Rights Management
Hoad, T.C. and Zobel, J.
Vast quantities of video data are distributed around the world every day. Video content owners would like to be able to automatically detect any use of their material, in any media or representation. We investigate techniques for identifying similar video content in large collections. Current methods are based on related technology, such as image retrieval, but the effectiveness of these techniques has not been demonstrated for the task of locating video clips that are derived from the same original. We propose anew method for locating video clips, shot-length detection, and compare it to methods based on image retrieval. We test the methods in a variety of contexts and show that they have different strengths and weaknesses. Our results show that the shot-based approach is promising, but is not yet sufficiently robust for practical application. |
Cite as: Hoad, T.C. and Zobel, J. (2003). Video Similarity Detection for Digital Rights Management. In Proc. Twenty-Sixth Australasian Computer Science Conference (ACSC2003), Adelaide, Australia. CRPIT, 16. Oudshoorn, M. J., Ed. ACS. 237-245. |
(from crpit.com)
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