A Novel Binocular Eye-Tracking SystemWith Stereo Stimuli for 3D Gaze Estimation

TL;DR

This paper introduces a binocular eye-tracking system with stereo stimuli that accurately estimates 3D gaze points, enhancing immersive 3D interaction without requiring users to wear accessories.

Contribution

It presents a novel 3D eye tracking device and a regression model that estimates 3D gaze using stereo stimuli and eye movement features, improving depth accuracy in gaze estimation.

Findings

Average 2D gaze error of 0.66°

3D point of gaze error of 1.85~cm/0.15~m

Effective in different stereo scene depths

Abstract

Eye-tracking technologies have been widely used in applications like psychological studies and human computer interactions (HCI). However, most current eye trackers focus on 2D point of gaze (PoG) estimation and cannot provide accurate gaze depth.Concerning future applications such as HCI with 3D displays, we propose a novel binocular eye tracking device with stereo stimuli to provide highly accurate 3D PoG estimation. In our device, the 3D stereo imaging system can provide users with a friendly and immersive 3D visual experience without wearing any accessories. The eye capturing system can directly record the users eye movements under 3D stimuli without disturbance. A regression based 3D eye tracking model is built based on collected eye movement data under stereo stimuli. Our model estimates users 2D gaze with features defined by eye region landmarks and further estimates 3D PoG with a multi source feature set constructed by comprehensive eye movement features and disparity features from stereo stimuli. Two test stereo scenes with different depths of field are designed to verify the model effectiveness. Experimental results show that the average error for 2D gaze estimation was 0.66\degree and for 3D PoG estimation, the average errors are 1.85~cm/0.15~m over the workspace volume 50~cm $\times$ 30~cm $\times$ 75~cm/2.4~m $\times$ 4.0~m $\times$ 7.9~m separately.