Eye finding via face detection for a foveated, active vision system
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Eyedraw: a system for drawing pictures with eye movements
Assets '04 Proceedings of the 6th international ACM SIGACCESS conference on Computers and accessibility
Eye tracking using neural network and mean-shift
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
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In this paper, an interface using eye and mouse for the handicapped people is proposed. The eye regions are localized using neural network (NN)-based texture classifier that discriminates the facial region into eye class and non-eye class, and then are tracked using mean-shift procedure. The mouse region is detected based on edge information and then tracked using template matching. To assess the validity of the proposed system, it was applied to the interface system and was tested on a group of 25 users. The results show that our system has the accuracy of 99%.