An efficient method for eye tracking and eye-gazed FOV estimation
Abstract
An eye-tracking integrated head-mounted display (ET-HMD) system can be used in many applications. Its complexity imposes great challenges on designing a compact, portable, and robust system. For an ET-HMD system, having accurate eye-gazed field-of-view (FOV) estimation and performing fast high-fidelity rendering only on the identified FOV is its crucial technique for augmented video/image/graphics display. In this paper, an energy-controlled iterative curve fitting method is proposed for accurate pupil detection and tracking. Based on a 3D eye model and the pupil tracking results, eye-gazed FOV can be identified precisely. The experimental results show that the average tracking error of using the proposed method is less than 0.5 degree for pupil rotation while the other conventional methods can only achieve 1.0 degree.