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    ARTICLE

    Human Behavior Classification Using Geometrical Features of Skeleton and Support Vector Machines

    Syed Muhammad Saqlain Shah1,*, Tahir Afzal Malik2, Robina khatoon1, Syed Saqlain Hassan3, Faiz Ali Shah4

    CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 535-553, 2019, DOI:10.32604/cmc.2019.07948

    Abstract Classification of human actions under video surveillance is gaining a lot of attention from computer vision researchers. In this paper, we have presented methodology to recognize human behavior in thin crowd which may be very helpful in surveillance. Research have mostly focused the problem of human detection in thin crowd, overall behavior of the crowd and actions of individuals in video sequences. Vision based Human behavior modeling is a complex task as it involves human detection, tracking, classifying normal and abnormal behavior. The proposed methodology takes input video and applies Gaussian based segmentation technique followed More >

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