Research on Fatigue Driving Monitoring Model and Key Technologies Based on Multi-input Deep Learning. Issue 2 (October 2020)

• Record Type: Journal Article
• Authors: Liu, Jinfeng; Li, Guang; Zhou, Jiyan; Lu, Dunlu; Chen, Bingchu; He, Feiyong
• Is Part Of: Journal of physics. Volume 1648:Issue 2 (2020)
• Publication Date: 2020-10
• Subjects: Fatigue Driving Monitoring Model -- Multi-input Deep Learning -- Eye State Recognition; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1648/2/022112
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Monitoring and controlling the driver's fatigue state plays an important role in reducing the traffic accident rate and traffic casualties caused by fatigue driving, so it has high research value and lay a technical foundation with the development of tech. Based on this, this paper first studies the key tech of fatigue driving monitoring based on vision, then analyses the driver's eye state recognition, and finally studies the driver's facial dynamic fatigue expression recognition and model establishment based on multi-input deep learning.