Eye plays an important role in collecting information of face characteristics. The eye region includes information of gesture, identity, gender and etc. It can be used in many applications such as gesture understanding, fatigue driving, eye blink detecting, disabled-helping domain, psychology domain, human-machine interaction, face recognition in video, and so on. Eye tracking is the focus problem in the researching domain of human-machine interaction. In this paper a new method of eye tracking is proposed because in older method detection algorithm has poor real time performance. This method combines the location and detection algorithm with the grey prediction for eye tracking. The model is used to predict the position of moving eye in the next frame, and then this position is taken as the reference point for the searching region of eye. Experimental results show that the grey prediction model can explore out the latest law of motion to overcome the shortcoming that a linear filter must assume the motion law in advance. Thus it can achieve robust tracking of eye. Furthermore it can build the real-time online grey prediction model under the polar coordinate system, making it unnecessary to convert the model.

Eye Tracking Blink Detection Fatigue Driving