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汽车安全与节能学报

汽车安全与节能学报 ›› 2010, Vol. 1 ›› Issue (3): 200-204.DOI: 10.3969/j.issn.1674-8484.2010.03.005

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基于面部表情特征的驾驶员疲劳状态识别

马添翼，成波   

  1. 清华大学 汽车安全与节能国家重点实验室，北京 100084
  • 收稿日期:2010-08-06 出版日期:2010-09-20 发布日期:2010-09-20
  • 通讯作者: 成波，教授。E-mail：chengbo@tsinghua.edu.cn
  • 作者简介:马添翼（1987－），女（汉），山东，硕士研究生。E-mail：matianyi1987@gmail.com
  • 基金资助:

    国家“八六三”高技术研究发展计划资助项目( 2009AA11Z214 )；

     清华大学汽车安全与节能重点实验室自主科研计划项目( zz2010-032 )

Detection of driver's drowsiness using facial expression features

MA Tianyi, CHENG Bo   

  1. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
  • Received:2010-08-06 Online:2010-09-20 Published:2010-09-20

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摘要： 建立了基于面部表情特征的疲劳状态识别方法并进行了验证。从疲劳表情机理以及人的经验知识两个角度出发挖掘出人在疲劳状态下的表情特征，将定性的特征量化得到11个疲劳表情描述指标作为判据。进行疲劳驾驶实验，通过标记点检测的方法获取特征指标数据，从中提取出4个在不同疲劳状态间有显著性差异的特征指标，分别为张眼程度、眉头下垂程度、嘴角下垂程度及嘴形弯曲程度，并通过疲劳表情机理以及人的经验知识对指标的变化规律进行验证。以此为基础建立了基于典型判别方程的判别算法，实现了对疲劳驾驶93%的检测精度。

关键词: 疲劳驾驶, 面部表情识别, 表情特征\疲劳检测 

Abstract: A method for detection of drowsiness using visual information of human facial expression was studied and tested. Facial expression features in the state of drowsiness were analyzed based on the characteristics of facial muscle movement and empirical knowledge, then 11 features were characterized. Fatigue driving experiments were conducted using a driving simulator. The features were obtained by the detection of facial markings. Four drowsy expression indexes with significant differences between different drowsy levels have been found, and a discriminating model for drowsiness prediction based on the four indexes has been established, which are eyes open width, eyebrow droop level, corners of the mouth droop level and mouth bending. The results show that the proposed method in this paper could reach an overall correct detection rate of 93%.

Key words: drowsy driving, facial expression detection, expression features, drowsiness detection

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