3D gaze estimation with a single camera without IR illumination

Abstract

This paper proposes a 3D eye gaze estimation and tracking algorithm based on facial feature tracking using a single camera. Instead of using the infrared (IR) lights and the corneal reflections (glint), this algorithm estimates the 3D visual axis using the tracked facial feature points. For this, we first introduce an extended 3D eye model which includes both the eyeball and the eye-corners. Based on this eye model, we derive the equations to solve for the 3D eyeball center, the 3D pupil center and the 3D visual axis, from which we can solve for the point of gaze after a one-time personal calibration. The experimental results show the accuracy of this algorithm is less than 3deg. Compared with the existing IR-based eye tracking methods, the proposed method is simple to setup and can work both indoor and outdoor.