Distracted driving is one of the main causes of vehicle collisions in the United States. Passively monitoring a driver's activities constitutes the basis of an automobile safety system that can potentially reduce the number of accidents by estimating the driver's focus of attention. This paper proposes an inexpensive vision-based system to accurately detect Eyes Off the Road (EOR). The system has three main components: 1) robust facial feature tracking; 2) head pose and gaze estimation; and 3) 3-D geometric reasoning to detect EOR. From the video stream of a camera installed on the steering wheel column, our system tracks facial features from the driver's face. Using the tracked landmarks and a 3-D face model, the system computes head pose and gaze direction. The head pose estimation algorithm is robust to nonrigid face deformations due to changes in expressions. Finally, using a 3-D geometric analysis, the system reliably detects EOR.


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    Titel :

    Driver Gaze Tracking and Eyes Off the Road Detection System


    Beteiligte:
    Vicente, Francisco (Autor:in) / Huang, Zehua (Autor:in) / Xiong, Xuehan (Autor:in) / De la Torre, Fernando (Autor:in) / Zhang, Wende (Autor:in) / Levi, Dan (Autor:in)


    Erscheinungsdatum :

    01.08.2015


    Format / Umfang :

    1625116 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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