21 July 2017 Real-time driver fatigue detection based on face alignment
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Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 1042003 (2017); doi: 10.1117/12.2282043
Event: Ninth International Conference on Digital Image Processing (ICDIP 2017), 2017, Hong Kong, China
Abstract
The performance and robustness of fatigue detection largely decrease if the driver with glasses. To address this issue, this paper proposes a practical driver fatigue detection method based on face alignment at 3000 FPS algorithm. Firstly, the eye regions of the driver are localized by exploiting 6 landmarks surrounding each eye. Secondly, the HOG features of the extracted eye regions are calculated and put into SVM classifier to recognize the eye state. Finally, the value of PERCLOS is calculated to determine whether the driver is drowsy or not. An alarm will be generated if the eye is closed for a specified period of time. The accuracy and real-time on testing videos with different drivers demonstrate that the proposed algorithm is robust and obtain better accuracy for driver fatigue detection compared with some previous method.
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Huanhuan Tao, Guiying Zhang, Yong Zhao, Yi Zhou, "Real-time driver fatigue detection based on face alignment", Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042003 (21 July 2017); doi: 10.1117/12.2282043; http://dx.doi.org/10.1117/12.2282043
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KEYWORDS
Facial recognition systems

Eye

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