Human Activity Inference Using Hierarchical Bayesian Network in Mobile Contexts

2011 ◽  
pp. 38-45 ◽  
Author(s):  
Young-Seol Lee ◽  
Sung-Bae Cho
Keyword(s):  
Bayesian Network ◽  
Human Activity ◽  
Hierarchical Bayesian

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

2014 ◽  
Vol 548-549 ◽  
pp. 1093-1097 ◽  
Author(s):  
Dong Yao Jia ◽  
Sheng Xiong Zou
Keyword(s):  
Bayesian Network ◽  
Monitoring System ◽  
Detection Accuracy ◽  
Hierarchical Bayesian ◽  
Threshold Method ◽  
Driver Fatigue ◽  
Head Region ◽  
Eyelid Closure ◽  
Fatigue Monitoring ◽  
Hierarchical Bayesian Method

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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