We present a unified framework for body and hand tracking, the output of which can be used for understanding simultaneously performed body-and-hand gestures. The framework uses a stereo camera to collect 3D images, and tracks body and hand together, combining various existing techniques to make tracking tasks efficient. In addition, we introduce a multi-signal gesture database: the NATOPS aircraft handling signals. Unlike previous gesture databases, this data requires knowledge about both body and hand in order to distinguish gestures. It is also focused on a clearly defined gesture vocabulary from a real-world scenario that has been refined over many years. The database includes 24 body-and-hand gestures, and provides both gesture video clips and the body and hand features we extracted.


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    Titel :

    Tracking body and hands for gesture recognition: NATOPS aircraft handling signals database


    Beteiligte:
    Song, Y. (Autor:in) / Demirdjian, D. (Autor:in) / Davis, R. (Autor:in)


    Erscheinungsdatum :

    2011


    Format / Umfang :

    7 Seiten, 18 Quellen




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch






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