Presenting a Human Pupil Orbit Model (HPOM) for Eye-Gaze Tracking

Abstract

Eye tracking technology has been continuously researched for application in various fields. In the past, studies have been conducted to interpret eye movements in 3D space in order to solve the problem of not being able to find the centre of rotation of the eye. In this paper, we propose a novel pre-processing method for eye-gaze tracking by monitoring the front of the face with a camera. Our method works regardless of the distance between the eye and the camera. The proposed method includes an analysis technique that simplifies conventional three-dimensional space analysis to two dimensions. The contribution this work presents is a method to simplify gaze direction detection. The errors in our model's estimations appear to be under 1 pixel. In addition, our approach has an execution time of less than 1 s, enabling an adaptive model that responds to user movements in real time. The proposed method was able to overcome various problems that methods in existing studies still suffer from, including accurately finding the rotational centre of the user's eye-ball. Moreover, even when a user's pupil can only be monitored from a distance, our approach still makes it possible to produce accurate estimations.