We focus on the visual sensory information to recognize human activity in form of hand-arm movements from a small, predefined vocabulary. We accomplish this task by means of a matching technique by determining the distance between the unknown input and a set of previously defined templates. A dynamic time warping algorithm is used to perform the time alignment and normalization by computing a temporal transformation allowing the two signals to be matched. The system is trained with finite video sequences of single gesture performances whose start and end-point are accurately known. Preliminary experiments are accomplished off-line and result in a recognition accuracy of up to 92%.


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    Titel :

    Dynamic time warping for off-line recognition of a small gesture vocabulary


    Beteiligte:
    Corradini, A. (Autor:in)


    Erscheinungsdatum :

    2001-01-01


    Format / Umfang :

    715437 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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