Video-based driver abnormal driver behavior detecting and risk control are incrementally well-liked nowadays, because it is important for ensuring the safety of drivers and people within the vehicles, and it is a necessary step in realizing automatic driving at this situation. Different researchers are proceeded with the detecting abnormal behavior of driver with the help of the capturing and detecting the face and objects in the hand of a driver through image and video process, but the standard algorithms are not efficient of detecting difficult temporary characteristics of driver behavior. In this paper, we have added a step to the existing mechanism which can track the user’s abnormal behavior and thus send the information to the owner of vehicle. We have used three deep learning models to detect the behavior of the driver. These three new fusion models help in designing the model building and thus helping in risk control and help traffic department.


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    Title :

    Video-Based Abnormal Driving Behavior Detection and Risk Control Using Machine Learning


    Additional title:

    Algorithms for Intelligent Systems


    Contributors:


    Publication date :

    2022-09-14


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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