Title :
Drowsy driver detection system using eye blink patterns
Author :
Danisman, Taner ; Bilasco, Ian Marius ; Djeraba, Chabane ; Ihaddadene, Nacim
Author_Institution :
LIFL, Univ. Lille 1, Lille, France
Abstract :
This paper presents an automatic drowsy driver monitoring and accident prevention system that is based on monitoring the changes in the eye blink duration. Our proposed method detects visual changes in eye locations using the proposed horizontal symmetry feature of the eyes. Our new method detects eye blinks via a standard webcam in real-time at 110fps for a 320×240 resolution. Experimental results in the JZU eye-blink database showed that the proposed system detects eye blinks with a 94% accuracy with a 1% false positive rate.
Keywords :
accident prevention; cameras; driver information systems; feature extraction; road safety; accident prevention system; automatic drowsy driver monitoring; drowsy driver detection system; eye blink pattern; webcam; Accuracy; Cameras; Computer vision; Databases; Driver circuits; Face; Real time systems; Eye blink detection; drowsiness detection; eye symmetry;
Conference_Titel :
Machine and Web Intelligence (ICMWI), 2010 International Conference on
Conference_Location :
Algiers
Print_ISBN :
978-1-4244-8608-3
DOI :
10.1109/ICMWI.2010.5648121