This article describes the relevance of developing methods and systems for detection photo-video violations of the Rules of the road. The proposed method includes several steps: 1) detecting of the three classes of objects on a video sequence (pedestrian crossing, a motor vehicle and a human on the pedestrian crossing; 2) tracking the trajectories of the vehicle and the human on the pedestrian crossing; 3) comparing the paths of the pedestrian and the vehicle and determining whether there has been a violation of the Rules of the road for a certain period of time. For real-time object detection, we used neural network YOLO V3.


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    Titel :

    Method of Automated Detection of Traffic Violation with a Convolutional Neural Network


    Beteiligte:
    Ibadov S.R. (Autor:in) / Kalmykov B.Y. (Autor:in) / Ibadov R.R. (Autor:in) / Sizyakin R.A. (Autor:in)


    Erscheinungsdatum :

    2019




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt


    Schlagwörter :


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