基于深度学习和微表情检测的防疲劳驾驶检测综述
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摘要
随着国家经济的迅速发展,基础设施日益完善,人民生活水平不断提高,安全出行成为一项重大的民生课题。很多交通事故都是由疲劳驾驶引起。目前,快速、精准检测疲劳驾驶成为一个热点研究问题。基于此,从传统疲劳驾驶检测方案的局限性出发,引出了基于深度学习和微表情检测的防疲劳驾驶检测方案,归纳总结了微表情检测流程和深度学习流程。
With the rapid development of national economy, the improvement of infrastructure and the improvement of people's living standards, safe travel has become a major livelihood issue. Many traffic accidents are caused by fatigue driving. At present, rapid and accurate detection of fatigue driving has become a hot research topic. Based on this, starting from the limitations of the traditional fatigue driving detection scheme, the anti-fatigue driving detection scheme based on deep learning and micro-expression detection is introduced, and the micro-expression detection process and deep learning process are summarized.
With the rapid development of national economy, the improvement of infrastructure and the improvement of people's living standards, safe travel has become a major livelihood issue. Many traffic accidents are caused by fatigue driving. At present, rapid and accurate detection of fatigue driving has become a hot research topic. Based on this, starting from the limitations of the traditional fatigue driving detection scheme, the anti-fatigue driving detection scheme based on deep learning and micro-expression detection is introduced, and the micro-expression detection process and deep learning process are summarized.
引文
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[3]赵磊.基于深度学习和面部多源动态行为融合的驾驶员疲劳检测方法研究[D].济南:山东大学,2018:154.
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[2]Royal D.NATIONAL SURVEY OF SPEEDING,UNSAFE,DISTRACTED AND DROWSY DRIVING ATTITUDESAND BEHAVIOR,2002.VOLUMEIII,METHODS[J].Nutrition Research,2003,23(11):1477-1487.
[3]赵磊.基于深度学习和面部多源动态行为融合的驾驶员疲劳检测方法研究[D].济南:山东大学,2018:154.
[4]Gepperth A R T.Object Detection and Feature Base Learning with Sparse Convolutional Neural Networks[M].Berlin:Springer,2006:221-232.
[5]曾鸽.基于深度学习的驾驶员疲劳状态检测研究[D].长沙:湖南大学,2018:69.