Audio-Based copy detection in the large-scale internet videos

Authors:
Hongliang Bai;Lezi Wang;Chong Huang;Wei Liu;Chengbin Zeng;Yuan Dong
Affiliations:
France Telecom Research & Development, Beijing, P.R. China;Beijing University of Posts and Telecommunications, P.R. China;Beijing University of Posts and Telecommunications, P.R. China;France Telecom Research & Development, Beijing, P.R. China;France Telecom Research & Development, Beijing, P.R. China;France Telecom Research & Development, Beijing, P.R. China, Beijing University of Posts and Telecommunications, P.R. China
Venue:
PCM'12 Proceedings of the 13th Pacific-Rim conference on Advances in Multimedia Information Processing
Year:
2012

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Abstract

With the large-scale internet video data explosion, the content-based copy detection (CCD) related application and research are significant and necessary. Beside the image-based CCD, the audio-based method has the advantage in its simpleness and efficiency. The article improves the recent methods on the audio-based copy detection. Three improvements are introduced in the study. Firstly, the CEPS-like feature is proposed to satisfy the different audio scale requirements in the feature extraction. Then, the flexible hash-based searching algorithm is presented to strengthen the querying robustness. Finally, the results-based fusion is introduced to take the advantages of the different features. The actual NDCR performances of the balanced profile vary in 0.223~0.460 in the TRECVID2011 copy detection database. The results outperform any single feature.