Research on fatigue detection algorithm of vehicle driver based on computer vision

Zengxi Wang; Bo Yu; Xia Pan; Chuanqi Qin

doi:10.1117/12.2655821

12 January 2023 Research on fatigue detection algorithm of vehicle driver based on computer vision

Zengxi Wang, Bo Yu, Xia Pan, Chuanqi Qin

Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 1250925 (2023) https://doi.org/10.1117/12.2655821
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China

Abstract

After years of research on traffic accidents, it has been proved that serious traffic accidents will be caused by drivers' poor state, inattention, fatigue and other conditions. Computer vision obtains the driver's body information and face information through visual recognition technology, compares and analyzes with a large number of face database information, judges the driver's state, and makes corresponding reminders and warnings, so as to achieve driving safety. In this paper, the infrared camera is used for real-time face recognition and key point detection, and a multi feature fatigue driving detection method is proposed. Combined with OpenCV, the eye, mouth and head spatial posture coordinate points of the human face are located, and the fatigue is determined according to the change degree of blinking, yawning and nodding. Finally, the fusion algorithm is used to synthesize the above fatigue characteristic factors for fatigue prediction. Experiments show that the accuracy of the algorithm is more than 96%, and it has good stability and anti-interference ability.

Citation Download Citation

Zengxi Wang, Bo Yu, Xia Pan, and Chuanqi Qin "Research on fatigue detection algorithm of vehicle driver based on computer vision", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 1250925 (12 January 2023); https://doi.org/10.1117/12.2655821

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KEYWORDS

Eye

Mouth

Head

Detection and tracking algorithms

Facial recognition systems

Data fusion

Ear

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