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Compact Video Description for Copy Detection with Precise Temporal Alignment

  • Matthijs Douze
  • Hervé Jégou
  • Cordelia Schmid
  • Patrick Pérez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6311)

Abstract

This paper introduces a very compact yet discriminative video description, which allows example-based search in a large number of frames corresponding to thousands of hours of video. Our description extracts one descriptor per indexed video frame by aggregating a set of local descriptors. These frame descriptors are encoded using a time-aware hierarchical indexing structure. A modified temporal Hough voting scheme is used to rank the retrieved database videos and estimate segments in them that match the query. If we use a dense temporal description of the videos, matched video segments are localized with excellent precision.

Experimental results on the Trecvid 2008 copy detection task and a set of 38000 videos from YouTube show that our method offers an excellent trade-off between search accuracy, efficiency and memory usage.

Keywords

Video Frame Average Precision Interest Point Dynamic Time Warping Local Descriptor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Matthijs Douze
    • 1
  • Hervé Jégou
    • 2
  • Cordelia Schmid
    • 1
  • Patrick Pérez
    • 3
  1. 1.INRIA GrenobleFrance
  2. 2.INRIA RennesFrance
  3. 3.Technicolor RennesFrance

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