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dc.contributor.authorRoopalakshmi, R.-
dc.contributor.authorRam Mohana Reddy, Guddeti-
dc.identifier.citation2011 IEEE 5th International Conference on Internet Multimedia Systems Architecture and Application, IMSAA 2011 - Conference Proceedings, 2011, Vol., , pp.-en_US
dc.description.abstractAcoustic features are robust and powerful in video description, but not fully exploited for the emerging Content-Based video Copy Detection (CBCD) methods. To solve this discrepancy, this paper proposes a new CBCD approach using audio spectral features compared to existing visual content based methods. The proposed method incorporates three stages: 1) Extraction of spectral descriptors including centroid and energy; 2) Integration of resultant features to compute highly informative spectral descriptive words; 3) Utilization of clustering approach to speed up the similarity matching process. The results tested on TRECVID-2008 dataset, demonstrate the improved detection accuracy of proposed method (up to 27.845%) compared to reference methods against various transformations such as fast forward, slow motion, mp3 compression, and multiband companding. � 2011 IEEE.en_US
dc.titleTowards a new approach to video copy detection using acoustic featuresen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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