The accurate localization of iris center is difficult since the outer boundary of iris is often occluded significantly by the eyelids. In order to solve this problem, an infrared light source un-coaxial with the camera is used to produce dark pupil image for pupil center estimation. Firstly, the 3D position of the center of cornea curvature, which is used as translational movement information of eyeball, is computed using two cameras and the coordinates of two cornea reflections on the cameras' imaging planes. Then, the relative displacement of pupil center from the projection of the cornea curvature center on 2D image is extracted, describing the rotational movement of the eyeball. Finally, the feature vector is mapped into coordinates of gazing point on the screen using artificial neural network. As for the eye region detection problem, two wide-view webcams are used, and adaptive boosting+active appearance model algorithm is adopted to limit the region of interest within a small area. The result of our experiment shows that the average root-mean-square error is 0.62 in horizontal direction and 1.05 in vertical direction, which demonstrates the effectiveness of our solution in eye gaze tracking.