@article{(Open Science Index):https://publications.waset.org/pdf/3209,
	  title     = {Eye Location Based on Structure Feature for Driver Fatigue Monitoring},
	  author    = {Qiong Wang},
	  country	= {},
	  institution	= {},
	  abstract     = {One of the most important problems to solve is eye
location for a driver fatigue monitoring system. This paper presents an
efficient method to achieve fast and accurate eye location in grey level
images obtained in the real-word driving conditions. The structure of
eye region is used as a robust cue to find possible eye pairs. Candidates
of eye pair at different scales are selected by finding regions which
roughly match with the binary eye pair template. To obtain real one,
all the eye pair candidates are then verified by using support vector
machines. Finally, eyes are precisely located by using binary vertical
projection and eye classifier in eye pair images. The proposed method
is robust to deal with illumination changes, moderate rotations, glasses
wearing and different eye states. Experimental results demonstrate its
effectiveness.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {4},
	  number    = {12},
	  year      = {2010},
	  pages     = {1840 - 1844},
	  ee        = {https://publications.waset.org/pdf/3209},
	  url   	= {https://publications.waset.org/vol/48},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 48, 2010},
	}