This paper describes a real-time non-intrusive prototype driver fatigue monitor. It uses remotely located CCD cameras equipped with active IR illuminators to acquire video images of the driver. Various visual cues typically characterizing the alertness of the driver are extracted in real time and systematically combined to infer the fatigue level of the driver. The visual cues employed characterize the eyelid movement, gaze movement, head movement, and facial expression. A probabilistic model is developed to model human fatigue and to predict fatigue based on the observed visual cues and the available contextual information. The simultaneous use of multiple visual cues and their systematic combination yields a much more robust and accurate fatigue characterization than using a single visual cue. The feasibility of our system is demonstrated using the synthetic data. Further validation of our system under real life fatigue conditions with human subjects shows that it was reasonably robust, reliable and accurate in fatigue characterization.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Real time and non-intrusive driver fatigue monitoring


    Beteiligte:
    Zhiwei Zhu, (Autor:in) / Qiang Ji, (Autor:in)


    Erscheinungsdatum :

    01.01.2004


    Format / Umfang :

    576807 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Non-intrusive and real time driver status monitoring

    Fouquet, J.E. / Haven, R.E. / Venkafesh, S. et al. | IEEE | 2004

    Freier Zugriff

    A real-time system for monitoring driver fatigue

    Li, Yao-hua / You, Feng / Chen, Kang et al. | Taylor & Francis Verlag | 2016


    A real-time system for monitoring driver fatigue

    Li, Yao-hua | Online Contents | 2016


    Non-Intrusive Driver Drowsiness Monitoring Via Artificial Neural Networks

    Culp, J. / El-Gindy, M. / Haque, M.A. et al. | British Library Conference Proceedings | 2008


    Non-Intrusive Driver Drowsiness Monitoring Via Artificial Neural Networks

    Culp, J. / El-Gindy, M. / Haque, M. A. | SAE Technical Papers | 2008