Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
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A Multiple Features Video Copy Detection Algorithm Based on a SURF Descriptor

  • Hou, Yanyan (College of Information Science and Engineering, Zaozhuang University) ;
  • Wang, Xiuzhen (College of Information Science and Engineering, Zaozhuang University) ;
  • Liu, Sanrong (College of Information Science and Engineering, Zaozhuang University)
  • Received : 2015.05.19
  • Accepted : 2016.01.19
  • Published : 2016.09.30
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Abstract

Considering video copy transform diversity, a multi-feature video copy detection algorithm based on a Speeded-Up Robust Features (SURF) local descriptor is proposed in this paper. Video copy coarse detection is done by an ordinal measure (OM) algorithm after the video is preprocessed. If the matching result is greater than the specified threshold, the video copy fine detection is done based on a SURF descriptor and a box filter is used to extract integral video. In order to improve video copy detection speed, the Hessian matrix trace of the SURF descriptor is used to pre-match, and dimension reduction is done to the traditional SURF feature vector for video matching. Our experimental results indicate that video copy detection precision and recall are greatly improved compared with traditional algorithms, and that our proposed multiple features algorithm has good robustness and discrimination accuracy, as it demonstrated that video detection speed was also improved.

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References

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