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@article{144864,
        author = {P Sravanthi and N.Sukumar},
        title = {Driverless Eyes off Road Detection System},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {5},
        pages = {305-308},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144864},
        abstract = {Distracted driving is one of the main causes of vehicle collisions. 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. The system computes head pose and gaze direction. The head pose estimation algorithm is robust to non-rigid face deformations due to changes in expressions. Finally, using video based continuous image the system reliably detects EOR. The proposed system does not require any driver-dependent calibration or manual initialization and works in real time, during the day and night. To validate the performance of the system in a real car environment, we conducted a comprehensive experimental evaluation under a wide variety illumination conditions, facial expressions, and individuals. Our system achieved above 90% EOR accuracy for all tested scenarios.},
        keywords = {Road, Detection, Driverless car, EOR},
        month = {},
        }