Driver Fatigue Monitoring Based on Head and Facial Features Using Hierarchical Bayesian Method

Dong Yao Jia; Sheng Xiong Zou

doi:10.4028/www.scientific.net/AMM.548-549.1093

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 548-549Driver Fatigue Monitoring Based on Head and Facial...

Driver Fatigue Monitoring Based on Head and Facial Features Using Hierarchical Bayesian Method

Abstract:

Because fatigue monitoring based on the image of the non-contact measurement is single and low accuracy, a novelty driver fatigue monitoring system based on multivariate hierarchical Bayesian network is proposed. The system mainly includes four modules following: face region detecting, eyelid closure judging, head region positioning, and fatigue analyzing. The eye region is positioned precisely by the method of gray projection function, the binary image which contains the whole eye information using self-adapting threshold method is obtained, and then driver fatigue monitoring system based on hierarchical Bayesian network is used to evaluate the fatigue level of the driver. The experimental results show that the fatigue monitoring accuracy is up to 90% in specific conditions, it’s effective to improve the detection accuracy compared to the other method.

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Periodical:

Applied Mechanics and Materials (Volumes 548-549)

Pages:

1093-1097

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.548-549.1093

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Online since:

April 2014

Authors:

Dong Yao Jia*, Sheng Xiong Zou

Keywords:

Fatigue Monitoring, Feature Analyzing, Hierarchical Bayesian Evaluation

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* - Corresponding Author

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