Visual words based spatiotemporal sequence matching in video copy detection

  • Authors:

  • Huamin Ren;Shouxun Lin;Dongming Zhang;Sheng Tang;Ke Gao

  • Affiliations:

  • Laboratory of Advanced Computing Research, Institute of Computing Technology, Chinese Academy of Sciences and Graduate University of Chinese Academy of Sciences, Beijing, China and Information Cen ...;Laboratory of Advanced Computing Research, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Laboratory of Advanced Computing Research, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Laboratory of Advanced Computing Research, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China;Laboratory of Advanced Computing Research, Institute of Computing Technology, Chinese Academy of Sciences and Graduate University of Chinese Academy of Sciences, Beijing, China

  • Venue:
  • ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
  • Year:
  • 2009

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Abstract

This paper proposes a novel content-based copy retrieval scheme for video copy identification. Its goal is to detect matches between a doubtful video and the ones stored in the database of the legal holders of the videos. Due to various transformations the copy may has, we use visual words vector as a representation of a frame which is based on SIFT descriptor. Unlike traditional Bag-of-Words (BoW) based approach applied in semantic retrieval, in which the temporal variation during the video is always neglected, our matching algorithm takes into account spatial and temporal distances between a query clip and the one in database. Experiments show robustness and effectiveness of our approach according to various single and compound transformations.