Efficient Measurement of the Eye Blinking by Using Decision Function for Intelligent Vehicles

Authors:
Ilkwon Park;Jung-Ho Ahn;Hyeran Byun
Affiliations:
Dept. Of Computer Science, Yonsei University, Seoul, 120-749, Korea;Dept. Of Computer & Media Engineering, Kangnam University, South Korea;Dept. Of Computer Science, Yonsei University, Seoul, 120-749, Korea
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Year:
2007

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Abstract

In this paper, we propose an efficient measurement of the eye blinking for drowsy driver detection system that is one of the driver safety systems for the intelligent vehicle. However, during the real driving in the daytime, driver's face is exposed to various illuminations. It makes too difficult to monitor driver's eye blinking. Therefore, we propose efficient formation of the cascaded form of Support Vector Machines (SVM) as eye verification to boost the accuracy of eye detection. Furthermore, for an efficient measurement of eye blinking, we newly define decision function that is based on the measure of eyelid movement and the weight generated by the eye classifier. In the experiments, we can show the reliable performance for our own test data acquired during a real driving in the various illumination conditions. Furthermore, through our proposed method, we use detected eye blinking for Drowsy Driver Detection System.