Real-time driver fatigue detection based on face alignment

Huanhuan Tao; Guiying Zhang; Yong Zhao; Yi Zhou

doi:10.1117/12.2282043

21 July 2017 Real-time driver fatigue detection based on face alignment

Huanhuan Tao, Guiying Zhang, Yong Zhao, Yi Zhou

Proceedings Volume 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017); 1042003 (2017) https://doi.org/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.

Citation Download Citation

Huanhuan Tao, Guiying Zhang, Yong Zhao, and 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); https://doi.org/10.1117/12.2282043

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