Driver fatigue prediction with eyelid related parameters by support vector machine

[1] Hamada T, Ito T, Adachi K, et al. Detecting method for drivers-drowsiness applicable to individual features [J]. IEICE Trans on Information and Systems,2004,E87-D (1):88-96 [2] Wierwille W W, Lewin M G, Fairbanks R J. Final reports: research on vehicle-based driver status/performance Monitoring, Part III . DOT HS 808 640, 1996 [3] Hayami T, Matsunaga K, Shidoji K, et al. Detecting drowsiness while driving by measuring eye movement-a pilot study In Proc 5th Int Conference on Intelligent Transportation Systems. USA: IEEE, 2002:156-161 [4] Ji Q, Yang X J. Real-time eye, gaze, and face pose tracking for monitoring driver vigilance [J]. Real-Time Imaging,2002, 8:357-377 [5] Liu X, Xu F L, Fujimura K. Real-time eye detection and tracking for driver observation under various light conditions IEEE Intelligent Vehicle Symposium. USA: IEEE, 2002:344-351 [6] Morris T L, Miller J C. Electrooculographic and performance indices of fatigue during simulated flight [J]. Biological Psychology, 1996,42:343-360 [7] Ji Q, Zhu Z Z,Lan P L. Real-time nonitrusive monitoring and prediction of driver fatigue [J]. IEEE Transactions on Vehicular Technology,2004, 53(4):1052-1068 [8] Caffier P P, Erdmann U,Ullsperger P. Experimental evaluation of eye-blink parameters as a drowsiness measure [J]. Eur J Appl Physiol,2003,89:319-325 [9] Burges C J C. A tutorial on support vector machines for pattern recognition [J]. Data Min Knowl Disc, 1998,2 (2):121-167 [10] Cristiannini N, Shawe-Taylor J. An introduction to support vector machines and other kernel-based learning methods[M]. Cambridge: Cambridge University Press, 2000 [11] kerstedt T, Gillberg M. Subjective and objective sleepiness in the active individual [J]. International Journal of Neuroscience,1990,52:29-37 [12] Chang C C, Lin C J. LIBSVM: a library for support vector machines . 2001,Taipei:National Taiwom University, http://www.csie.ntu.edu.tw/cjlin/libsvm