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Automatic Labeling of Sports Video Using Umpire Gesture Recognition

  • Graeme S. Chambers
  • Svetha Venkatesh
  • Geoff A. W. West
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3138)

Abstract

We present results on an extension to our approach for automatic sports video annotation. Sports video is augmented with accelerometer data from wrist bands worn by umpires in the game. We solve the problem of automatic segmentation and robust gesture classification using a hierarchical hidden Markov model in conjunction with a filler model. The hierarchical model allows us to consider gestures at different levels of abstraction and the filler model allows us to handle extraneous umpire movements. Results are presented for labeling video for a game of Cricket.

Keywords

Gesture Recognition Accelerometer Data Sport Video Hand Gesture Recognition Gesture Data 
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 2004

Authors and Affiliations

  • Graeme S. Chambers
    • 1
  • Svetha Venkatesh
    • 1
  • Geoff A. W. West
    • 1
  1. 1.Department of ComputingCurtin University of TechnologyPerth

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