One of the important causes of traffic accidents is driver fatigue. In this paper, a new real-time non-intrusive method to detect driver fatigue is proposed. Firstly, face region is detected by AdaBoost algorithm because of its robustness. Then a region of interest of the eye is defined based on face geometry. In this region, eye pupil is precisely located by radial symmetry transform. With principal component analysis (PCA), three eigen spaces are trained to recognize eye states. Open, closed eye samples and other non-eye samples in the face region are used to get these eigen spaces. At last, PERCLOS and consecutive eye closure time are adopted to detect driver fatigue. Experiments with thirty two participants in realistic driving condition show the reliability and the robustness of our system.


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    Titel :

    Real-Time Driver Fatigue Detection Based on Eye State Recognition


    Beteiligte:
    Sun, Chao (Autor:in) / Li, Jian-hua (Autor:in) / Song, Yang (Autor:in) / Jin, Lai (Autor:in)


    Erscheinungsdatum :

    2013


    Format / Umfang :

    9 Seiten




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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