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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    Title :

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


    Contributors:
    Xuetao Zhang, (author) / Nanning Zheng, (author) / Fei Wang, (author) / Yongjian He, (author)


    Publication date :

    2011-07-01


    Size :

    271097 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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