WASET
	@article{(Open Science Index):https://publications.waset.org/pdf/10001635,
	  title     = {Driver Fatigue State Recognition with Pixel Based Caveat Scheme Using Eye-Tracking},
	  author    = {K. Thulasimani and  K. G. Srinivasagan},
	  country	= {},
	  institution	= {},
	  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.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {8},
	  number    = {11},
	  year      = {2014},
	  pages     = {2089 - 2094},
	  ee        = {https://publications.waset.org/pdf/10001635},
	  url   	= {https://publications.waset.org/vol/95},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 95, 2014},
	}