Study On Eye Gaze Tracking Using One Camera

Eye gaze tracking is one of the key techniques of the intelligent interface in the future between human and computerized devices and has widespread prospects of application in industry control, robotics and clinical medicine. The technique of eye-gaze tracking, based on corneal reflection and image processing, has the advantage of unobtrusiveness and has made considerable headway in recent years. However, owing to that it is also a developing technique and the characters of the eye movement, there are still many unresolved problems preventing the use of non-intrusive eye gaze systems in actual applications. The most prevalent of these are: accuracy, restricted head movement, robustness, and ease of calibration. To solve these problems, the technique of single camera remote eye gaze tracking has been studied; the constraints on the user's head imposed by most existing eye trackers have been significantly relaxed. The accuracy and robustness of the eye gaze tracking system have been improved.The main innovative researches in this paper are as follows:1. A single camera remote eye-gaze tracking technique is proposed to calculate the gaze direction by the relationship between the positions of the pupil center and three corneal reflections, the calibration parameters can be automatically adjusted to allow free head movements. Also, robust feature detection algorithms are developed. The system can work under natural head movements and show high accuracy and very good robustness.2. The image capturing system of the eye-gaze tracking technique is studied, a real-time eye tracking method and an automatic adjusting method for object lens of CCD camera in combining the aperture regulation with zooming and focusing are proposed. This system can track the eye from a head-should image and acquire clear images of the magnified eye in real time by the adaptive regulation of the CCD camera in different external lightings and user position conditions. The drawback of intensive labor is eliminated and the accuracy is improved.3. The algorithms to detect and locate the pupil in eye images are studied. Also a sub-pixel ellipse contour detection algorithm is proposed in order to locate the center of the pupil accurately in IR image of the eye. The proposed algorithm achieved sub-pixel accuracy, which will significantly enhance the performance of the eye-gaze tracking system.4. A method is presented to detect the user's eye blinks and to classify the eye as either open or closed at each frame of a real-time video stream of the face. A high success rate of detection is obtained using the proposed method, which can be used for fatigue monitoring and eye-controlled mouse.