Eye-tracking for detection of driver fatigue

被引:0
|
作者
Eriksson, M [1 ]
Papanikolopoulos, NP [1 ]
机构
[1] Univ Minnesota, Dept Comp Sci, Artificial Intelligence Robot & Vis Lab, Minneapolis, MN 55455 USA
关键词
driver fatigue; eye-tracking; template matching;
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
In this paper, we describe a system that locates and tracks the eyes of a driver. The purpose of such a system is to perform detection of driver fatigue. By mounting a small camera inside the car, we can monitor the face of the driver and look for eye-movements which indicate that the driver is no longer in condition to drive. In such a case, a warning signal should be issued. This paper describes how to find and track the eyes. We also describe a method that can determine if the eyes are open or closed. The primary criterion for the successful implementation of this system is that it must be highly non-intrusive. The system should start when the ignition is turned on Without having the driver initiate the system. Nor should the driver be responsible for providing any feedback to the system. The system must also operate regardless of the texture and the color of the face. It must also be able to handle diverse conditions, such as changes in light, shadows, reflections, etc.
引用
收藏
页码:314 / 319
页数:2
相关论文
共 50 条
  • [31] Driver Fatigue Detection based on Eye State Recognition
    Zhang, Fang
    Su, Jingjing
    Geng, Lei
    Xiao, Zhitao
    2017 INTERNATIONAL CONFERENCE ON MACHINE VISION AND INFORMATION TECHNOLOGY (CMVIT), 2017, : 105 - 110
  • [32] Driver Fatigue Detection based on Eye State Analysis
    Du, Yong
    Ma, Peijun
    Su, Xiaohong
    Zhang, Yingjun
    PROCEEDINGS OF THE 11TH JOINT CONFERENCE ON INFORMATION SCIENCES, 2008,
  • [33] A New Detecting and Tracking Method in Driver Fatigue Detection
    Yu, Yang
    Li, Xiaobin
    Sun, Haiyan
    PROCEEDINGS OF THE 2015 CHINESE INTELLIGENT SYSTEMS CONFERENCE, VOL 1, 2016, 359 : 123 - 129
  • [34] A Real-Time Driver Fatigue Detection System Based on Eye Tracking and Dynamic Template Matching
    Horng, Wen-Bing
    Chen, Chih-Yuan
    JOURNAL OF APPLIED SCIENCE AND ENGINEERING, 2008, 11 (01): : 65 - 72
  • [35] Eye Tracking based Real-Time Non-Interfering Driver Fatigue Detection System
    Rehman, Hamza Ur
    Naeem, Mohsin
    Khan, Masam
    Sikander, Gulbadan
    Anwar, Shahzad
    PROCEEDINGS OF THE 2018 10TH INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTERS AND ARTIFICIAL INTELLIGENCE (ECAI), 2018,
  • [36] Change detection in desktop virtual environments: An eye-tracking study
    Karacan, Hacer Uke
    Cagiltay, Kursat
    Tekman, H. Gurkan
    COMPUTERS IN HUMAN BEHAVIOR, 2010, 26 (06) : 1305 - 1313
  • [37] Parametric and Nonparametric Analysis of Eye-Tracking Data by Anomaly Detection
    Jansson, Daniel
    Rosen, Olov
    Medvedev, Alexander
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2015, 23 (04) : 1578 - 1586
  • [38] A Pilot Study of Smartphone Eye-Tracking for Detection of Positional Nystagmus
    Bastani, Pouya
    Phillips, Vidith
    Rieiro, Hector
    Badihian, Shervin
    Otero-Millan, Jorge
    Farrell, Nathan
    Newman-Toker, David
    Tehrani, Ali Saber
    ANNALS OF NEUROLOGY, 2024, 96 : S286 - S286
  • [39] A local optical flow eye-tracking method for depression detection
    Li, Yang
    Zhang, Xiang
    Zhang, Xianmin
    Zhu, Benliang
    Ye, Xin
    AIP ADVANCES, 2023, 13 (09)
  • [40] Deception detection by means of eye-tracking in the concealed information test
    Pavlov, Y. G.
    Zlokazov, K. V.
    INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY, 2018, 131 : S160 - S160