This paper presents a nonintrusive prototype computer vision system for real-time fatigue driving detection. First, we use Haar-like features to detect a driver’s face and conduct tracking by introducing an improved Camshift algorithm. Second, we propose a new eye-detection algorithm that combines the Adaboost algorithm with template matching to reduce computational costs and add an eye-validation process to increase the accuracy of the detection rate. Third, and different from other methods focusing on detecting eyes using the ‘bright pupil’ effect, which only works well only for certain constrained lighting conditions, our method detects and estimates the iris center in the hue (H) channel of the hue, saturation, value color space and fits the iris with an ellipse. After extracting the eye fatigue features, we calculate the PERCLOS measurement for fatigue evaluation. This system has been tested on the IMM Face Database, which contains more than 200 faces, and in a real-time test. The experimental results show that the system possesses good accuracy and robustness.


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    Title :

    A real-time system for monitoring driver fatigue


    Contributors:
    Li, Yao-hua (author) / You, Feng (author) / Chen, Kang (author) / Huang, Ling (author) / Xu, Jian-min (author)

    Published in:

    Publication date :

    2016-11-16


    Size :

    12 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    A real-time system for monitoring driver fatigue

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    Real time and non-intrusive driver fatigue monitoring

    Zhiwei Zhu, / Qiang Ji, | IEEE | 2004


    Real-time Driver Fatigue Detection System

    Jain, Ashish / Gandotra, Rahil / Madan, Tushar et al. | Tema Archive | 2014


    Eye Detection for a Real-Time Vehicle Driver Fatigue Monitoring System

    Coetzer, R. / Hancke, G. / Institute of Electrical and Electronics Engineers | British Library Conference Proceedings | 2011