Study of the Eye-tracking Methods Based on Video

Author

Mei, Zhan ; Liu, Jihong ; Li, Zhongfan ; Yang, Li

Author_Institution

Coll. of Comput. Sci. & Eng., Shenyang Univ. of Chem. Technol., Shenyang, China

fYear

2011

fDate

26-28 July 2011

Firstpage

1

Lastpage

5

Abstract

Driver fatigue is a chief cause of the traffic accidents. The key technologies for detecting driver fatigue are the real-time and effectively detecting and tracking of driver´s eyes. This paper studies the eye-tracking methods by the images of the driver´s face based on video cameras. Firstly, a Haar cascade classifier for the face is designed on the arithmetic of Viola-Jones and AdaBoost. Then the eye-tracking is realized by two-step location methods. The experimental results show that the methods discussed in this paper are accurate and robust.

Keywords

Haar transforms; driver information systems; eye; face recognition; image classification; object tracking; road accidents; road traffic; video cameras; AdaBoost; Haar cascade classifier; Viola-Jones; driver eyes; driver face; driver fatigue detection; eye-tracking methods; traffic accidents; two-step location methods; video cameras; Complexity theory; Face; Fatigue; Feature extraction; Image edge detection; Real time systems; Training; driver fatigue; eye location; face location;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence, Communication Systems and Networks (CICSyN), 2011 Third International Conference on

Conference_Location

Bali

Print_ISBN

978-1-4577-0975-3

Electronic_ISBN

978-0-7695-4482-3

Type

conf

DOI

10.1109/CICSyN.2011.14

Filename

6005665