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Proceedings Paper

Real-time driver fatigue detection based on face alignment
Author(s): Huanhuan Tao; Guiying Zhang; Yong Zhao; Yi Zhou
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Paper 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.

Paper Details

Date Published: 21 July 2017
PDF: 6 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 1042003 (21 July 2017); doi: 10.1117/12.2282043
Show Author Affiliations
Huanhuan Tao, Peking Univ. Shenzhen Graduate School (China)
Guiying Zhang, Zunyi Medical Univ. (China)
Yong Zhao, Peking Univ. Shenzhen Graduate School (China)
Yi Zhou, Peking Univ. Shenzhen Graduate School (China)

Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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