Improved video-based eye-gaze detection method

Abstract

Recently, some video-based eye-gaze detection methods used in eye-slaved support systems for the severely disabled have been studied. In these methods, infrared light was irradiated to an eye, two feature areas (the corneal reflection light and pupil) were detected in the image obtained from a video camera and then the eye-gaze direction was determined by the relative positions between the two. However, there were problems concerning stable pupil detection under various room light conditions. In this paper, methods for precisely detecting the two feature areas are consistently mentioned. First, a pupil detection technique using two light sources and the image difference method is proposed. Second, for users wearing eye glasses, a method for eliminating the images of the light sources reflected in the glass lens is proposed. The effectiveness of these proposed methods is demonstrated by using an imaging board. Finally, the feasibility of implementing hardware for the proposed methods in real time is discussed.