Tracking the Evolution of a Tennis Match Using Hidden Markov Models

  • Ilias Kolonias
  • William Christmas
  • Josef Kittler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3138)


The creation of a cognitive perception systems capable of inferring higher-level semantic information from low-level feature and event information for a given type of multimedia content is a problem that has attracted many researchers’ attention in recent years. In this work, we address the problem of automatic interpretation and evolution tracking of a tennis match using standard broadcast video sequences as input data. The use of a hierarchical structure consisting of Hidden Markov Models is proposed. This will take low-level events as its input, and will produce an output where the final state will indicate if the point is to be awarded to one player or another. Using hand-annotated data as input for the classifier described, we have witnessed 100% of the points correctly awarded to the players.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Ilias Kolonias
    • 1
  • William Christmas
    • 1
  • Josef Kittler
    • 1
  1. 1.Center for Vision, Speech and Signal ProcessingUniversity of SurreyGuildfordUK

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