This paper proposesSathyabama, B. an intelligent traffic surveillance system thatDevpura, Ashutosh detects the vehicle and its speed, colour, direction,Maroti, Mayank and type of vehicle using computer vision and deepRajput, Rishabh Singh learning. This information can be used to find the traffic violator using automatic number plate recognition. Research shows that over-speeding accounts for 60% of total accidents in India, which raises a serious concern. The proposed approach uses TensorFlow object detection API for vehicle detection, cumulative Vehicle counting, and colour detection of the vehicle using colour histogram integrated with the KNN machine learning algorithm in a real-time environment and a robust approach using deep learning and computer vision for speed estimation and direction detection. This study will effectively monitor traffic usage and help officials track, detect, and lay a floor plan to effectively stop speeding and wrong-side driving vehicles from getting into accidents. This paper proposed an efficient and robust approach for detecting moving vehicles along with their speed and other attributes. The proposed approach can be integrated with a pre-installed traffic monitoring camera system without significant adjustments.


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    Titel :

    Vehicle Speed Estimation and Tracking Using Deep Learning and Computer Vision


    Weitere Titelangaben:

    Lecture Notes on Data Engineering and Communications Technologies


    Beteiligte:
    Raj, Jennifer S. (Herausgeber:in) / Kamel, Khaled (Herausgeber:in) / Lafata, Pavel (Herausgeber:in) / Sathyabama, B. (Autor:in) / Devpura, Ashutosh (Autor:in) / Maroti, Mayank (Autor:in) / Rajput, Rishabh Singh (Autor:in)


    Erscheinungsdatum :

    24.02.2022


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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