A Robust 3D Eye Gaze Tracking System using Noise Reduction

This paper describes a novel real-time 3D gaze estimation system. The system consists of two cameras and two IR light sources. There are three novelties in this method. First, in our system, two IR lights are mounted near the centers of the stereo cameras, respectively. Based off this specific configuration, the 3D position of the corneal center can be simply derived by the 3D reconstruction technique. Then, after extracting the 3D position of the "virtual pupil" correctly, the optical axis of the eye can be obtained directly by connecting the "virtual pupil" with the corneal center. Second, we systematically analyze the noise in our 3D gaze estimation algorithm and propose an effective constraint to reduce this noise. Third, to estimate the user-dependent parameters (i.e. the constraint parameters and the eye parameters), a simple calibration method is proposed by gazing at four positions on the screen. Experimental results show that our system can accurately estimate and track eye gaze under natural head movement.