Abstract
In this chapter, a vision system for monitoring driver vigilance is presented. The level of vigilance is determined by integrating a number of facial parametric values including: percentage of eye closure over time, average eye closure duration, eye blinking frequency, average degree of gaze, average duration of mouth openness and head nodding frequency. Initially, facial features including the eyes, mouth and head are first located in the input video sequence. They are then tracked over subsequent images. Facial parameters are estimated during facial feature tracking. A number of video sequences having drivers of both sex and of different ages under various illuminations and road conditions are employed to test the performance of the proposed system. Finally, we suggest future work on how to extend the system in terms of both efficiency and effectiveness.
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Chen, SW., Yao, KP., Lin, HW. (2012). Sleep Technology for Driving Safety. In: Chiang, RY., Kang, SC. (eds) Introduction to Modern Sleep Technology. Intelligent Systems, Control and Automation: Science and Engineering, vol 64. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5470-6_12
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DOI: https://doi.org/10.1007/978-94-007-5470-6_12
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