Accurate Eye Tracking from Dense 3D Surface Reconstructions using Single-Shot Deflectometry

Fuente: arXiv
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Main Authors: Wang, Jiazhang, Wang, Tianfu, Xu, Bingjie, Cossairt, Oliver, Willomitzer, Florian
Format: Preprint
Published: 2023
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author Wang, Jiazhang
Wang, Tianfu
Xu, Bingjie
Cossairt, Oliver
Willomitzer, Florian
author_facet Wang, Jiazhang
Wang, Tianfu
Xu, Bingjie
Cossairt, Oliver
Willomitzer, Florian
contents Eye-tracking plays a crucial role in the development of virtual reality devices, neuroscience research, and psychology. Despite its significance in numerous applications, achieving an accurate, robust, and fast eye-tracking solution remains a considerable challenge for current state-of-the-art methods. While existing reflection-based techniques (e.g., "glint tracking") are considered to be very accurate, their performance is limited by their reliance on sparse 3D surface data acquired solely from the cornea surface. In this paper, we rethink the way how specular reflections can be used for eye tracking: We propose a novel method for accurate and fast evaluation of the gaze direction that exploits teachings from single-shot phase-measuring-deflectometry(PMD). In contrast to state-of-the-art reflection-based methods, our method acquires dense 3D surface information of both cornea and sclera within only one single camera frame (single-shot). For a typical measurement, we acquire $>3000 \times$ more surface reflection points ("glints") than conventional methods. We show the feasibility of our approach with experimentally evaluated gaze errors on a realistic model eye below only $0.12^\circ$. Moreover, we demonstrate quantitative measurements on real human eyes in vivo, reaching accuracy values between only $0.46^\circ$ and $0.97^\circ$.
format Preprint
id arxiv_https___arxiv_org_abs_2308_07298
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Accurate Eye Tracking from Dense 3D Surface Reconstructions using Single-Shot Deflectometry
Wang, Jiazhang
Wang, Tianfu
Xu, Bingjie
Cossairt, Oliver
Willomitzer, Florian
Computer Vision and Pattern Recognition
Human-Computer Interaction
Optics
Eye-tracking plays a crucial role in the development of virtual reality devices, neuroscience research, and psychology. Despite its significance in numerous applications, achieving an accurate, robust, and fast eye-tracking solution remains a considerable challenge for current state-of-the-art methods. While existing reflection-based techniques (e.g., "glint tracking") are considered to be very accurate, their performance is limited by their reliance on sparse 3D surface data acquired solely from the cornea surface. In this paper, we rethink the way how specular reflections can be used for eye tracking: We propose a novel method for accurate and fast evaluation of the gaze direction that exploits teachings from single-shot phase-measuring-deflectometry(PMD). In contrast to state-of-the-art reflection-based methods, our method acquires dense 3D surface information of both cornea and sclera within only one single camera frame (single-shot). For a typical measurement, we acquire $>3000 \times$ more surface reflection points ("glints") than conventional methods. We show the feasibility of our approach with experimentally evaluated gaze errors on a realistic model eye below only $0.12^\circ$. Moreover, we demonstrate quantitative measurements on real human eyes in vivo, reaching accuracy values between only $0.46^\circ$ and $0.97^\circ$.
title Accurate Eye Tracking from Dense 3D Surface Reconstructions using Single-Shot Deflectometry
topic Computer Vision and Pattern Recognition
Human-Computer Interaction
Optics
url https://arxiv.org/abs/2308.07298