Sign language is the primary modality of communication among deaf and mute society all over the world. This paper proposes a viewpoint independent method for sign recognition. Considering that two sequences of the same sign can be roughly considered as the input of a stereo vision system after time-warping, and the fundamental matrix associated with two views should be unique, we can convert the temporal-spatial recognition task as a verification task within a stereo vision framework. After time-warping of the input sequences, the proposed framework can reach both temporal and viewpoint invariance. We demonstrate the efficiency of the proposed framework by recognizing a vocabulary of 100 words of Chinese sign language. The recognition rate is up to 97% at rank 3. Furthermore, the proposed framework can be easily extended to other recognition tasks, such as gait recognition and lip-reading recognition.


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    Titel :

    Viewpoint invariant sign language recognition


    Beteiligte:
    Qi Wang, (Autor:in) / Xilin Chen, (Autor:in) / Liangguo Zhang, (Autor:in) / Chunli Wang, (Autor:in) / Wen Gao, (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    209640 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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