As amounts of publicly available video data grow the need to query this data efficiently becomes significant. Consequently content-based retrieval of video data turns out to be a challenging and important problem. We address the specific aspect of inferring semantics automatically from raw video data. In particular, we introduce a new video data model that supports the integrated use of two different approaches for mapping low-level features to high-level concepts. Firstly, the model is extended with a rule-based approach that supports spatio-temporal formalization of high-level concepts, and then with a stochastic approach. Furthermore, results on real tennis video data are presented, demonstrating the validity of both approaches, as well us advantages of their integrated use.


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    Titel :

    Content-based video retrieval by integrating spatio-temporal and stochastic recognition of events


    Beteiligte:
    Petkovic, M. (Autor:in) / Jonker, W. (Autor:in)


    Erscheinungsdatum :

    01.01.2001


    Format / Umfang :

    936104 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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