In this paper, we propose an automatic system that recognizes driver's abnormal behavior, i.e. cell phone use. Driver's actions are captured using a camera mounted above the dash board. Then the observed features are input into a Hidden Conditional Random Fields (HCRF) model. To incorporate long range dependencies, features are collected within a local window from neighbor sites. We evaluate the presented algorithm on the real video segments, and the results show that the system can successfully recognize the behavior.


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    Titel :

    Visual recognition of driver hand-held cell phone use based on hidden CRF


    Beteiligte:
    Xuetao Zhang, (Autor:in) / Nanning Zheng, (Autor:in) / Fei Wang, (Autor:in) / Yongjian He, (Autor:in)


    Erscheinungsdatum :

    01.07.2011


    Format / Umfang :

    271097 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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