A robust 3D eye gaze tracking system using noise reduction

Abstract

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 on 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.

Optics of the human cornea influence the accuracy of stereo eye-tracking methods: a simulation study

“…In these set-ups the internal camera parameters such as the focal length are known, as well as the position and orientation of the cameras and light sources. Other researchers have proposed similar 3D methods to compute the optical axis of the eye from the pupil center and corneal reflections (e.g [15], see [13] for an overview of the different approaches). Alternative methods have been proposed that estimate the optical axis from the shape of the limbus [16], ellipse descriptions of the pupil contour combined with conic algebra [17], or corneal reflections and pupil center combined with pupil-contour data [18].…”

“…In general, it is assumed that the entrance pupil lies in front of the actual pupil, that the entrance pupil is slightly larger, and that the optical axis goes through the center of the actual pupil and the entrance pupil. Chen et al investigated this assumption through ray-tracing for a stereocamera set-up and found small deviations of the virtual pupil, with a resulting error in simulated gaze estimates of 0.08 degrees on average [15]. However, they applied a simplified geometrical model of the eye, in which the cornea was modelled as a convex sphere with only one refractive surface.…”

Gaze Estimation Method Involving Corneal Reflection-Based Modeling of the Eye as a General Surface of Revolution about the Optical Axis of the Eye

“…To compare our method to the method that uses a spherical model of the cornea, we also calculated the POG by using Chen's method [11] at the same time. Chen's method uses a spherical model of the cornea and the same arrangement of cameras and light sources as our system.…”

“…It passes through C j and intersects the camera image plane at a point P j j . If the cornea is perfectly spherical, the line connecting L j and P j j would pass through A, and the position of A can be easily determined using two cameras as described in Chen's method [11]. However, the position of A cannot be accurately estimated when light is reflected from around an edge of the surface of the cornea.…”

“…For example, in Fig. 6 the line connecting P 00 and C 0 and the line connecting P 11 and C 1 do not intersect on the optical axis of the eye.…”