In this paper, a multi-view face pose classification method is introduced. Each face region is normalized by two eye-centers and mouth center, and then multi-class classifiers are trained for face pose classification. The face pose classification is organized into a tree structure that deals with off-image plane pose variation. As a specific application in video, it can estimate the face pose in each frame that results in a face pose variation trajectory, which may have important applications such as in security monitoring of car drivers. Experiment results on a very large set compared with a PCA reconstruction method as a benchmark are reported to show its effectiveness.


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    Titel :

    Multi-view face pose classification by tree-structured classifier


    Beteiligte:
    Zhiguang Yang, (Autor:in) / Haizhou Ai, (Autor:in) / Okamoto, T. (Autor:in) / Shihong Lao, (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    547351 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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