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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    Title :

    Viewpoint invariant sign language recognition


    Contributors:
    Qi Wang, (author) / Xilin Chen, (author) / Liangguo Zhang, (author) / Chunli Wang, (author) / Wen Gao, (author)


    Publication date :

    2005-01-01


    Size :

    209640 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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