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基于UKF非线性人眼跟踪的驾驶员疲劳检测

张祖涛 张家树

张祖涛, 张家树. 基于UKF非线性人眼跟踪的驾驶员疲劳检测[J]. 西南交通大学学报, 2008, 21(6): 697-702.
引用本文: 张祖涛, 张家树. 基于UKF非线性人眼跟踪的驾驶员疲劳检测[J]. 西南交通大学学报, 2008, 21(6): 697-702.
ZHANG Zutao, ZHANG Jiashu. Driver Fatigue Detection Based on Unscented Kalman Filter and Eye Tracking[J]. Journal of Southwest Jiaotong University, 2008, 21(6): 697-702.
Citation: ZHANG Zutao, ZHANG Jiashu. Driver Fatigue Detection Based on Unscented Kalman Filter and Eye Tracking[J]. Journal of Southwest Jiaotong University, 2008, 21(6): 697-702.

基于UKF非线性人眼跟踪的驾驶员疲劳检测

基金项目: 

教育部新世纪优秀人才支持计划资助项目(NCET-05-0794)

西南交通大学机械工程学院青年教师基金(MYF0806)的资助

详细信息
    作者简介:

    张祖涛(1974- ),男,讲师,博士研究生,主要从事图像与视频处理、生物特征识别与智能交通应用研究.E-mail:zzt@home.swjtu.edu.cn

Driver Fatigue Detection Based on Unscented Kalman Filter and Eye Tracking

  • 摘要: 为解决驾驶员疲劳检测算法中头部快速移动、人眼非线性跟踪以及实际疲劳表情的识别问题,提出了一种新的基于UKF眼跟踪算法的驾驶员疲劳检测方法.根据近似非线性函数的概率分布比近似其函数更容易的原则,利用UT无迹变换,选择一组确定的Sigma点集逼近驾驶员人眼运动状态的后验概率密度函数,进行人眼非线性跟踪.在驾驶员人眼非线性跟踪基础上,通过计算PERCLOS值,进行现实驾驶条件下驾驶员疲劳的跟踪检测.实验结果表明,该方法不仅可以增强对驾驶员头部旋转、快速移动以及光照变换的鲁棒性,而且可以比传统的Kalm an滤波算法提供更精确的计算估计.

     

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出版历程
  • 收稿日期:  2007-05-09
  • 刊出日期:  2008-12-25

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