DocumentCode
3290547
Title
A New Real-Time Eye Tracking for Driver Fatigue Detection
Author
Zhang, Zutao ; Zhang, Jiashu
Author_Institution
Key Lab of Signal & Inf. Process., Southwest Jiaotong Univ., Sichuan
fYear
2006
fDate
38869
Firstpage
8
Lastpage
11
Abstract
Driver fatigue is one of the important factors that cause traffic accidents. The vision-based facial expression recognition technique is the most prospective method to detect driver fatigue. In this paper, we present a new driver fatigue detection based on unscented Kalman filter and eye tracking in this paper. The face is located using Haar algorithm firstly, which has good robustness in terms of head motions, variable lighting conditions, the change of hair and having glasses, etc. Secondly, the geometric properties and projection technique are used for eye location. Thirdly, we propose a new real time eye tracking method based on unscented Kalman Filter. Finally, driver fatigue can be detected whether the eyes are closed over 5 consecutive frames using vertical projection matching. The experimental results show validity of our method for driver fatigue detection under variable realistic conditions
Keywords
Kalman filters; accident prevention; computer vision; eye; face recognition; feature extraction; image matching; image motion analysis; image texture; road accidents; tracking filters; Haar algorithm; driver fatigue detection; facial expression recognition technique; geometric properties; hair change; head motion; real-time eye tracking; traffic accident; unscented Kalman filter; variable lighting condition; vertical projection matching; vision-based technique; Change detection algorithms; Eyes; Face detection; Face recognition; Fatigue; Glass; Hair; Road accidents; Robustness; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
ITS Telecommunications Proceedings, 2006 6th International Conference on
Conference_Location
Chengdu
Print_ISBN
0-7803-9587-5
Electronic_ISBN
0-7803-9587-5
Type
conf
DOI
10.1109/ITST.2006.288748
Filename
4068517
Link To Document