Commenced in January 2007
Paper Count: 30178
Driver Fatigue State Recognition with Pixel Based Caveat Scheme Using Eye-Tracking
Abstract:Driver fatigue is an important factor in the increasing number of road accidents. Dynamic template matching method was proposed to address the problem of real-time driver fatigue detection system based on eye-tracking. An effective vision based approach was used to analyze the driver’s eye state to detect fatigue. The driver fatigue system consists of Face detection, Eye detection, Eye tracking, and Fatigue detection. Initially frames are captured from a color video in a car dashboard and transformed from RGB into YCbCr color space to detect the driver’s face. Canny edge operator was used to estimating the eye region and the locations of eyes are extracted. The extracted eyes were considered as a template matching for eye tracking. Edge Map Overlapping (EMO) and Edge Pixel Count (EPC) matching function were used for eye tracking which is used to improve the matching accuracy. The pixel of eyeball was tracked from the eye regions which are used to determine the fatigue state of the driver.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1107053Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1308
 T. C. Chieh, M. M. Mustafa, A. Hussain, E. Zahedi, B. Y. Majlis, “Driver Fatigue Detection Using Steering Grip Force”, Proc. IEEE Student Conference on Research and Development, Putrajaya, Malaysia, 2003, pp.45-48.
 K. J. Cho, B. Roy, S. Mascaro, and H. H. Asada, “A Vast DOF Robotic Car Seat Using SMA Actuators with a Matrix Drive System,” Proc. IEEE Robotics and Automation, New Orleans, LA, USA, Vol.4, 2004, pp.3647- 3652.
 R. C. Coetzer and G. P. Hancke, “Eye Detection for a Real-Time Vehicle Driver Fatigue Monitoring System,” Proc. 2011 IEEE Intelligent Vehicles Symposium, Baden-Baden, Germany, 2011, pp. 66- 71.
 W. Dong and X. Wu, “Driver Fatigue Detection Based on the Distance of eyelid,” Proc. IEEE VLSI Design and Video Technology, Suzhou, China, 2005, pp. 365-368.
 H. Gu, Q. Ji, and Z. Zhu, “Active Facial Tracking for Fatigue Detection", Proc. 6th IEEE Workshop on Applications of Computer Vision, Orlando, FL, USA, 2002, pp. 137-142.
 H. Gu and Q. Ji, “An Automated Face Reader for Fatigue Detection,” Proc. 6th IEEE International Conference on Automatic Face and Gesture Recognition, Seoul, Korea, 2004, pp.111-116.
 W. B. Horng and C. Y. Chen, “A Real-Time Driver Fatigue Detection System Based on Eye Tracking and Dynamic Template Matching.” Tamkang Journal of Science and Engineering, Vol.11, No.1, 2008, pp.65-72.
 R.C. Gonzalez and R.E. Woods, Digital Image Processing, Second Edition, Prentice Hall, Upper Saddle River, NJ, USA, 2002.
 T. Ito, S. Mita, K. Kozuka, T. Nakano, and S.Yamamoto, “Driver Blink Measurement by the Motion Picture Processing and Its Application to Drowsiness Detection,” Proc. IEEE 5th International Conference on Intelligent Transportation Systems, Singapore, 2002, pp. 168-173.
 Q. Ji, Z. Zhu, and P. Lan, “Real-Time Nonintrusive Monitoring and Prediction of Driver Fatigue,” IEEE Transactions on Vehicular Technology, Vol.53, No.4, 2004, pp.1052-1068.
 M. A. Recarte and L. M. Nunes, “Effects of Verbal and Spatial-Imagery Tasks on Eye Fixations while Driving,” Journal of Experimental Psychology: Applied, Vol.6, No.1, 2000, pp.31-43.
 Smart Motorist, Inc., “Driver Fatigue is an Important Cause of Road Crashes”, http://www.smartmotorist.com/traffic-and-safety-guideline// driver-fatigue-is-an-important-cause-of-road crashes.html.
 H. Wang, L. B. Zhou, and Y. Ying, “A Novel Approach for Real Time Eye State Detection in Fatigue Awareness System,” Proc. 2010 IEEE International Conference on Robotics Automation and Mechatronics, 2010, Singapore, pp. 528-532.
 J. H. Yang, Z. H. Mao, L. Tijerina, T. Pilutti, J. F. Coughlin, and E. Feron, “Detection of Driver Fatigue Caused by Sleep Deprivation,” IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, Vol. 39, No. 4, 2009, pp. 694-705.
 K. P. Yao, W. H. Lin, C. Y. Fang, J. M. Wang, S.L. Chang, and S. W. Chen, “Real-Time Vision-Based Driver Drowsiness/Fatigue Detection system, Proc. IEEE 71st Vehicular Technology Conference, Taipei, Taiwan, 2010, pp. 1-5.