Research on Fatigue Driving State Recognition Method Based on Multi-feature Fusion

被引：0
|
作者：
Hu F. [1 ]
Cheng Z. [1 ]
Xu Q. [1 ]
Peng Q. [1 ]
Quan X. [1 ]
机构：
[1] College of Computer Science and Electronic Engineering, Hunan University, Changsha
来源：
Hunan Daxue Xuebao/Journal of Hunan University Natural Sciences | 2022年 / 49卷 / 04期
关键词：
Blink of an eye state recognition; Driving safety; Fatigue recognition; Feature point positioning; Multiple feature fusion;
D O I：
10.16339/j.cnki.hdxbzkb.2022274
中图分类号：
学科分类号：
摘要：
Aiming at the problem of fatigue driving state recognition in traffic safety, the recognition rate of using a single fatigue driving feature is low. This paper studies and proposes a fatigue recognition method based on the weighted sum of facial multi-features. The eye fatigue parameters, such as continuous eye closing time, eye closing frame ratio and blink frequency, are extracted by human eye state detection algorithm. The number and duration of yawning are obtained through yawning state detection, the nodding frequency is obtained through head motion state analysis, and a driving fatigue state detection model integrating the above six characteristics is established to evaluate the driver's fatigue level and give the corresponding early warning. The experimental test data are selected from part of the NTHU driver fatigue detection video data set. After experimental adjustment, it is found that this method has high recognition accuracy and provide a good recognition effect. © 2022, Editorial Department of Journal of Hunan University. All right reserved.
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页码：100 / 107
页数：7
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