A Novel Binocular Eye-Tracking SystemWith Stereo Stimuli for 3D Gaze Estimation
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by
Jinglin Sun, Zhipeng Wu, Han Wang, Peiguang Jing, Yu Liu
2021
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 0.66and
for 3D PoG estimation, the average errors are 1.85 cm/0.15 m over the workspace
volume 50 cm × 30 cm × 75 cm/2.4 m × 4.0 m × 7.9 m
separately.
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