The paper proposes an advanced driver-assistance system that correlates the driver's head pose to road hazards by analyzing both simultaneously. In particular, we aim at the prevention of rear-end crashes due to driver fatigue or distraction. We contribute by three novel ideas: Asymmetric appearance-modeling, 2D to 3D pose estimation enhanced by the introduced Fermat-point transform, and adaptation of Global Haar (GHaar) classifiers for vehicle detection under challenging lighting conditions. The system defines the driver's direction of attention (in 6 degrees of freedom), yawning and head-nodding detection, as well as vehicle detection, and distance estimation. Having both road and driver's behaviour information, and implementing a fuzzy fusion system, we develop an integrated framework to cover all of the above subjects. We provide real-time performance analysis for real-world driving scenarios.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Look at the Driver, Look at the Road: No Distraction! No Accident!


    Beteiligte:
    Rezaei, Mahdi (Autor:in) / Klette, Reinhard (Autor:in)


    Erscheinungsdatum :

    2014-06-01


    Format / Umfang :

    1253446 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Driver distraction

    Kinnear, Neale / Stevens, Alan | ELBA - Bundesanstalt für Straßenwesen (BASt) | 2017

    Freier Zugriff

    Driver distraction

    Skewes, D. | British Library Online Contents | 1997


    Driver distraction determination

    OLSSON CLAES / GONZALEZ PINTOR SEBASTIAN / BRANNLUND OLLE | Europäisches Patentamt | 2020

    Freier Zugriff

    DRIVER DISTRACTION DETERMINATION

    OLSSON CLAES / GONZALEZ PINTOR SEBASTIAN / BRÄNNLUND OLLE | Europäisches Patentamt | 2020

    Freier Zugriff