Facial expression recognition can be divided into three steps: face detection, expression feature extraction and expression categorization. Facial expression feature extraction and categorization are the most key issue. To address this issue, we propose a method to combine local binary pattern (LBP) and embedded hidden markov model (EHMM), which is the key contribution of this paper. This paper first gives an introduction about facial expression recognition and then describes EHMM and LBP. Finally, we give out the LBP-EHMM method in facial expression recognition, and perform an experiment to obtain a comparison between LBP feature and discrete cosine transform (DCT) feature.


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    Title :

    Facial Expression Recognition Based on LBP-EHMM


    Contributors:
    Cao, Jianqiang (author) / Tong, Can (author)


    Publication date :

    2008-05-01


    Size :

    367321 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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