• DocumentCode
    2401748
  • Title

    Action snippets: How many frames does human action recognition require?

  • Author

    Schindler, Konrad ; Van Gool, Luc

  • Author_Institution
    BIWI, ETH Zurich, Zurich
  • fYear
    2008
  • fDate
    23-28 June 2008
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Visual recognition of human actions in video clips has been an active field of research in recent years. However, most published methods either analyse an entire video and assign it a single action label, or use relatively large look-ahead to classify each frame. Contrary to these strategies, human vision proves that simple actions can be recognised almost instantaneously. In this paper, we present a system for action recognition from very short sequences (ldquosnippetsrdquo) of 1-10 frames, and systematically evaluate it on standard data sets. It turns out that even local shape and optic flow for a single frame are enough to achieve ap90% correct recognitions, and snippets of 5-7 frames (0.3-0.5 seconds of video) are enough to achieve a performance similar to the one obtainable with the entire video sequence.
  • Keywords
    image classification; image motion analysis; image recognition; image sequences; video signal processing; action recognition; action snippets; human action recognition; human vision; video clips; visual recognition; Feature extraction; Humans; Image motion analysis; Layout; Legged locomotion; Shape; Surveillance; Video sequences; Visual databases; Voting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on
  • Conference_Location
    Anchorage, AK
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4244-2242-5
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2008.4587730
  • Filename
    4587730