This paper describes a new method of facial expression recognition based on independent component analysis (ICA) and eigen-space method. We had proposed eigen-space method based on class-features (EMC), and EMC was the outstanding method with classification accuracy superior to multiple discriminant analysis (MDA). Our new method, GEMC, is a generalization of EMC by using ICA technique. GEMC has discriminated the facial expression class in a precision 10 or more points higher than conventional methods (EMC, MDA and ICA) because of classification experiments.


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    Titel :

    Facial expression analysis by generalized eigen-space method based on class-features (GEMC)


    Beteiligte:
    Eguchi, I. (Autor:in) / Kotani, K. (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    351974 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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