Driver Drowsiness Detection by Identification of Yawning and Eye Closure

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Zohoorian Yazdi Mina; SORYANI MOHSEN

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Journal Paper

Paper Information

Journal: Automotive Science and Engineering Year:2019 | Volume:9 | Issue:3 Page(s): 3033-3044

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Information Journal Paper

Title

Driver Drowsiness Detection by Identification of Yawning and Eye Closure

Author(s)

Zohoorian Yazdi Mina | SORYANI MOHSEN | Issue Writer Certificate

Keywords

Active Contour

Driver Drowsiness

Deep Learning

Depth Information

Eyes State

RGB_D

Yawning Detection

Abstract

Today most accidents are caused by drivers’ fatigue, drowsiness and losing attention on the road ahead. In this paper, a system is introduced, using RGB-D cameras to automatically identify drowsiness and give warning. In this system two important modules have been utilized simultaneously to identify the state of driver’ s mouth and eyes for detecting drowsiness. At first, using the Depth Information, the mouth area and its state are identified. Then using CNN networks, to predict whether the eyes are open or closed, a semi-VGG architecture is used. The results of yawning and Eyes States detection are integrated to decide whether an alarm should be issued. The results show an accuracy of about 90% which is encouraging.

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APA: Copy

Zohoorian Yazdi, Mina, & SORYANI, MOHSEN. (2019). Driver Drowsiness Detection by Identification of Yawning and Eye Closure. AUTOMOTIVE SCIENCE AND ENGINEERING (INTERNATIONAL JOURNAL OF AUTOMOTIVE ENGINEERING), 9(3), 3033-3044. SID. https://sid.ir/paper/321849/en

Vancouver: Copy

Zohoorian Yazdi Mina, SORYANI MOHSEN. Driver Drowsiness Detection by Identification of Yawning and Eye Closure. AUTOMOTIVE SCIENCE AND ENGINEERING (INTERNATIONAL JOURNAL OF AUTOMOTIVE ENGINEERING)[Internet]. 2019;9(3):3033-3044. Available from: https://sid.ir/paper/321849/en

IEEE: Copy

Mina Zohoorian Yazdi, and MOHSEN SORYANI, “Driver Drowsiness Detection by Identification of Yawning and Eye Closure,” AUTOMOTIVE SCIENCE AND ENGINEERING (INTERNATIONAL JOURNAL OF AUTOMOTIVE ENGINEERING), vol. 9, no. 3, pp. 3033–3044, 2019, [Online]. Available: https://sid.ir/paper/321849/en

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