Algorithm Research On Eye Tracking And Gaze Detection

Computer vision as such a challenging field has enormous development potential. It has been attracting many researchers who explore and do intensive study on it. With the development of computer performance and popularity of electronic product, more and more researchers work at the human eye detection which is the important research interest in the fields of computer vision. Eye detection and eye tracking technologies can be used for fatigue detection, human-machine interaction for the disabled, visual game and so on.The main research content of this paper is divided into three parts, including eye detection,eye tracking and gaze detection,An appropriate method of eye detection for video image and a practical gaze tracking method are used based on the intensive research of related algorithm. And a real-time eye tracking and gaze detection system is constructed in VC.First, Adaboost face detection algorithm is used to detect face, at the same time, an effective paradigm to cope with big view angle and planar rotated face is proposed. Finally, the face and eyes are detected accurately and in real-time. On the basis of face detection, this paper finds some rectangular features that is suitable with eyes, and with these features the Adaboost cascade classifiers are trained for eye detection.Because the region of the pupil is relatively stable in the eye screenshot image and the pupil's feature are obvious, so this paper locates the pupil firstly, then, eye blink classifier is trained to detect the blink status of the eyes, at the same time, eye corner is detected accuratly , this is the foundation for gaze tracking.Second, we can track eyes after finding eyes, the paper brings a Kalman filter into the particle filter, which is used to predict and revise in the sampling stage. This method can reduce the number of particles needed in tracking, and realize the purpose that tracks eyes quickly and exactly.Finally, this paper proposes a novel method for computing the eye-gaze direction and position in the eye-gaze tracking system. The eye corner is applied as the reference point instead of mark and Purkinje points in traditional ones. The difference of the moving point and the reference one is employed to compute the eye-gaze direction and position in the presented method. The center of iris is explored as the moving point due to that it can accurately reflect the moving state of eye. The eye corner is exploited as the reference point due to that it is the most stable point and relatively insensitive to facial expressions. The proposed method overcomes the shortcomings of conventional ones that adopt the mark and Purkinje as the reference points, and it does not need users to mark the marks on faces and allow the moderate variations of hear pose. Experimental results indicate that the method of the eye corner locating is fast and precise. In this way, the relative distance problem of eye motion arising in the eye-gaze tracking system can be well handled.The eye tracking and human-machine interaction system of this paper achieves the real-time eye detection and gaze tracking. And with the information of intentional blink we achieve the human-machine interaction. The system has good robustness to a certain illumination change, light side face and head tilt, but it needn't high-level hardware condition. The method of the system is different from current dominant principle. It has a quality with low cost and high efficiency.