We present our techniques and results on automatic analysis of tennis video to facilitate content-based retrieval. Our approach is based on the generation of an image model for the tennis court-lines. We derive this model by using the knowledge about dimensions and connectivity (form) of a tennis court and typical camera geometry used when capturing a tennis video. We use this model to develop: a court line detection algorithm; and a robust player tracking algorithm to track the tennis players over the image sequence. We also present a color-based algorithm to select tennis court clips from an input raw footage of tennis video. Automatically extracted tennis court lines and the players' location information are analyzed in a high-level reasoning module and related to useful high-level tennis play events. Results on real tennis video data are presented demonstrating the validity and performance of the approach.


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    Titel :

    Automatic classification of tennis video for high-level content-based retrieval


    Beteiligte:
    Sudhir, G. (Autor:in) / Lee, J.C.M. (Autor:in) / Jain, A.K. (Autor:in)


    Erscheinungsdatum :

    01.01.1998


    Format / Umfang :

    1282191 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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