American Society of Civil Engineers


Driver’s Eyes Detection and Tracking System Using Two Cameras


by Lingling Li, (Automatic Technology & Intelligent Control Center, Department of Electronic Information & Control Engineering, Beijing University of Technology, P.O. Box 424, Beijing, ST 100124. E-mail: lingling-li1984@163.com), Yangzhou Chen, (Automatic Technology & Intelligent Control Center, Department of Electronic Information & Control Engineering, Beijing University of Technology. E-mail: yzchen@bjut.edu.cn), and Le Xin, (Automatic Technology & Intelligent Control Center, Department of Electronic Information & Control Engineering, Beijing University of Technology. E-mail: xinle@bjut.edu.cn)
Section: Intelligent Transportation Systems and Technology, pp. 2098-2108, (doi:  http://dx.doi.org/10.1061/41127(382)226)

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Document type: Conference Proceeding Paper
Part of: ICCTP 2010: Integrated Transportation Systems: Green, Intelligent, Reliable
Abstract: Driver fatigue is an important cause of combination-unit traffic crashes and eyes are an important factor to embody driver’s fatigue degree. At present, almost all of driver’s eyes detecting and tracking systems are based on one camera. Such system of detecting and tracking eyes’ features will give very lower accuracy. So a method of driver’s eyes detection and tracking system using two cameras is proposed in this paper. It is based on a controllable camera and a fixed camera and the two cameras can communicate through serial port. The main principle is to collect the monitoring video of the cabin through camera A (shoot driver’s upper body) at first, then locate the driver’s face using rapid image processing algorithm in camera A. After that we control camera B (just shoot driver’s face) through serial port according to face position in camera A and make it shoot driver’s face all the time. At last, a new method which is based on combined Adaboost algorithm, particle filter and prior knowledge was applied to track driver’s eyes in camera B.


ASCE Subject Headings:
Driver behavior
Imaging techniques
Traffic accidents