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n-Grams of Action Primitives for Recognizing Human Behavior

  • Christian Thurau
  • Václav Hlaváč
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4673)

Abstract

This paper presents a novel approach for behavior recognition from video data. A biologically inspired action representation is derived by applying a clustering algorithm to sequences of motion images. To obey the temporal context, we express behaviors as sequences of n-grams of basic actions. Novel video sequences are classified by comparing histograms of action n-grams to stored histograms of known behaviors. Experimental validation shows a high accuracy in behavior recognition.

Keywords

Video Sequence IEEE Computer Society Action Recognition Temporal Context Sport Video 
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 2007

Authors and Affiliations

  • Christian Thurau
    • 1
  • Václav Hlaváč
    • 1
  1. 1.Czech Technical University, Faculty of Electrical Engineering, Department for Cybernetics, Center for Machine Perception, 121 35 Prague 2, Karlovo náměstíCzech Republic

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