Development Of An Eye-Blink Detection System To Monitor Drowsiness Of Automobile Drivers
Keywords:
Drowsiness, blink detection, blinks frequency, drowsiness detection, fatigueAbstract
This paper presents a study that employed human-computer interaction (HCI) in the development of an improved driver’s drowsiness detection system (DDS) for monitoring the drowsiness of car drivers. The basic process used motion analysis technique for eye detection, which involves the analysis of the involuntary blinks of a user of the system. After the system had been initialized, the eye was tracked using the square difference matching method. The major parameter subsequently used to detect drowsiness was the frequency of blinks, such that an alarm is triggered when it gets to a critical level. The results demonstrated that a low cost webcam, with a capture rate of 30 frames/s and resolution of 320 x 240, was used to achieve a blink accuracy of 94.8%, missed blink error of 2.4%, false positive error of 3%. Also, an eye tracking accuracy of 72% at a distance of about 30cm was obtained. An improvement on the accuracy and reliability of this system over existing ones was achieved.
References
Chau, M. and Betke, V., “Real Time Eye Tracking and Blink Detection with USB”, Boston University Computer Science Technical Report, 2005.
Danisman, T., Bilasco, I.M., Djeraba, C., Ihaddadene, N. “Drowsy driver detection system using blinks patterns”, In Machine and Web Intelligence (ICMWI), 2010 International Conference, 230-233, 5th Oct 2010.
Galley, N. and Schleicher, R. “Subjective and Optomotoric Indicators of Driver Drowsiness”, 3rd International Conference on Traffic and Transport Psychology, Nottingham, UK, 1-7, 2004.
Grauman, K., Betke, M., Gips, J. and Bradski, G.. “Communication via eye blinks - detection and duration analysis in real time”, Proceedings of the IEEE Computer Vision and Pattern Recognition Conference (CVPR 2001), Kauai, Hawaii, 2(1): 1010–1017, 2001.
Http://www.nashruddeen.com, “Real Time Eye Tracking and Blink Detection”, Available Online, Accessed July 16, 2009.
Ji, Q., Zhu, Z. and Lan, P., “Real-Time Nonintrusive Monitoring and Prediction of Driver Fatigue”, IEEE Transactions on Vehicular Technology, 53(4): 1052-1067, July 2004.
National Transportation Safety Board. Safety (NTSB), “Fatigue, alcohol, other drugs, and medical factors in fatal-to-the driver heavy truck crashes”, National Transportation and Safety Board. Safety Study, NTST/SS-90/01, 1990.
National Transportation Safety Board. Safety (NTSB), Factors that affect fatigue in heavy truck accidents. National Transportation Safety Board. Safety Study, NTSB/SS-95/01, 1995.
Rosekind, M. R., “Managing Fatigue in Transportation: No Magic Bullet”, Hearing on Fatigue and Its Safety Effects on the Commercial Motor Vehicle and Railroad Industries. United States Senate, Committee on Commerce, Science and Transportation, September 16, 1998.
Sullivan, J. J., “Fighting Fatigue”, Public Roads, Federal Highway Administration, U.S. Department of Transportation, 67(2):1-5, 2003.
Thorslund, B., “Electrooculogram Analysis and Development of a System for Defining Stages of Drowsiness”, Linköping University, Linköping, 2003.
Wang, J. S. and Knipling, R. R., “Single vehicle roadway departure crashes, Problem size assessment and statistical description”, DOT HS 808113, US Department of Transportation, 1994
Weirwille, W.W., “Overview of Research on Driver Drowsiness Definition and Driver Drowsiness Detection”, 14th International Technical Conference on Enhanced Safety of Vehicles, 23-26, October 1994.
