Citation

Azman, Afizan and Jai Raman, Kirbana and Ibrahim, Siti Zainab and Azli Abdullah, Mohd Fikri and Abdul Razak, Siti Fatimah and Muhamad Amin, Anang Hudaya and Arumugam, Venosha and Yogarayan, Sumendra and Sonaimuthu, Kalaiarasi (2018) Fatigue Monitoring Based on Yawning and Head Movement. In: 2018 6th International Conference on Information and Communication Technology (ICoICT), 3-5 May 2018, Bandung, Indonesia.

Text 08528759.pdf - Published Version Restricted to Repository staff only Download (2MB)

Abstract

Driver fatigue is one of the main reasons causing traffic accidents. Yawning is an important character of driver fatigue. Mouth geometric character represents state of driver. So driver's mouth detection and information extraction is especially important. This paper proposes to locate and track driver's yawning based on mouth using camera to detect driver's fatigue in driving environment. Then contour algorithm features to detect driver's yawning and track it according to historical position. At last, yawning is detected by the ratio of mouth in the name of dark region as when he mouth is widely open. Through this method the resolution ratios which are transferred to percentage of driver's mouth is higher than one camera and the feature information to be more accuracy. The head movement is partially a phase where the fatigue would be detected by using face detection itself to detect the head movement. In order to get a clear vision of driver's fatigue, yawning and head movement activity will be the best to detect in a driving environment since it provides a better basis for driver fatigue judging.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	fatigue,yawn detection,head movement,contour method
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA630-695 Structural engineering (General)
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	10 Mar 2021 19:16
Last Modified:	10 Mar 2021 19:16
URII:	http://shdl.mmu.edu.my/id/eprint/7382

Downloads

Edit (login required)