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An efficient content based video copy detection using the sample based hierarchical adaptive k-means clustering

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Abstract

Content-based video copy detection (CBCD) is very important for video copyright protection in view of the growing popularity of video sharing websites, which deals with not only whether a copy occurs in a query video stream but also where the copy is located and where the copy is originated from. In this paper, we present a video copy detection scheme based on local features which can deal with very large databases both in terms of quality and speed. First, we propose a new clustering algorithm to build “visual words” efficiently. Since our CBCD framework performs indexing using tree structures of cluster centers, the proposed clustering algorithm can improve the quality of retrieval and greatly shrink the off-line training time. Then, we introduce a TF-IDF (term frequency–inverse document frequency) weighted BOF (bag-of-features) voting retrieval method for matching video frames, which is robust to significant video distortion and efficient in terms of memory usage and computation time. Furthermore, we present a verification step robustly inspecting the temporal consistency between the query video and the corresponding candidate videos to further improve the accuracy of retrieval. The experimental results show that the proposed video copy detection scheme achieves high localization accuracy, while achieving comparable performance compared with state-of-the-art copy detection methods.

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Acknowledgments

The authors would like to thank the anonymous reviewers for valuable comments. This work was supported by funds from National Natural Science Foundation of China (NSFC Projects No. 61173110 and No. 11272253).

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Authors and Affiliations

  1. School of Printing and Packaging Engineering, Xi’an University of Technology, Xi’an, China

    Kaiyang Liao

  2. School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China

    Kaiyang Liao & Guizhong Liu

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  1. Kaiyang Liao
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  2. Guizhong Liu
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Correspondence to Guizhong Liu.

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Liao, K., Liu, G. An efficient content based video copy detection using the sample based hierarchical adaptive k-means clustering. J Intell Inf Syst 44, 133–158 (2015). https://doi.org/10.1007/s10844-014-0332-5

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  • DOI: https://doi.org/10.1007/s10844-014-0332-5

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