After years of research on traffic accidents, it has been proved that serious traffic accidents will be caused by drivers' poor state, inattention, fatigue and other conditions. Computer vision obtains the driver's body information and face information through visual recognition technology, compares and analyzes with a large number of face database information, judges the driver's state, and makes corresponding reminders and warnings, so as to achieve driving safety. In this paper, the infrared camera is used for real-time face recognition and key point detection, and a multi feature fatigue driving detection method is proposed. Combined with OpenCV, the eye, mouth and head spatial posture coordinate points of the human face are located, and the fatigue is determined according to the change degree of blinking, yawning and nodding. Finally, the fusion algorithm is used to synthesize the above fatigue characteristic factors for fatigue prediction. Experiments show that the accuracy of the algorithm is more than 96%, and it has good stability and anti-interference ability.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Research on fatigue detection algorithm of vehicle driver based on computer vision


    Contributors:
    Wang, Zengxi (author) / Yu, Bo (author) / Pan, Xia (author) / Qin, Chuanqi (author)

    Conference:

    Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022) ; 2022 ; Guangzhou,China


    Published in:

    Proc. SPIE ; 12509


    Publication date :

    2023-01-12





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Computer Vision Based Driver Assistance Drowsiness Detection

    Emashharawi, Maryam J. S. / Khalifa, Othman O. / Abdul Malik, Noreha et al. | Springer Verlag | 2021


    Driver Fatigue Detection Algorithm Research Based on the Characteristics of Eyes

    Wang, Qin ;Tang, Lan ;Yang, Kun | Trans Tech Publications | 2014


    Software Centric Driver Fatigue Discernment System Using Computer Vision

    Agrawal, Meghna / Kumar, Rishabh / Das, Nripendra Narayan | IEEE | 2022


    An Embedded Driver Fatigue Detect System Based on Vision

    Shen, Huaming / Xu, Meihua / Ran, Feng | Springer Verlag | 2017