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Gaze Error Estimation and Linear Transformation to Improve Accuracy of Video-Based Eye Trackers

Lookup NU author(s): Varun Padikal, Dr Penny LawtonORCiD, Dr Laura YoungORCiD, Professor Jenny ReadORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

© 2025 by the authors.Eye tracking technology plays a crucial role in various fields such as psychology, medical training, marketing, and human–computer interaction. However, achieving high accuracy over a larger field of view in eye tracking systems remains a significant challenge, both in free viewing and in a head-stabilized condition. In this paper, we propose a simple approach to improve the accuracy of video-based eye trackers through the implementation of linear coordinate transformations. This method involves applying stretching, shearing, translation, or their combinations to correct gaze accuracy errors. Our investigation shows that re-calibrating the eye tracker via linear transformations significantly improves the accuracy of video-based tracker over a large field of view.

Publication metadata

Author(s): Padikal V, Plonkowski A, Lawton PF, Young LK, Read JCA

Publication type: Article

Publication status: Published

Journal: Vision

Year: 2025

Volume: 9

Issue: 2

Online publication date: 03/04/2025

Acceptance date: 21/03/2025

Date deposited: 08/07/2025

ISSN (electronic): 2411-5150

Publisher: MDPI

URL: https://doi.org/10.3390/vision9020029

DOI: 10.3390/vision9020029

Data Access Statement: The data presented in this paper the accuracy of EyeLink 1000 Plus and Tobii Pro Nano can be found at here: https://doi.org/10.25405/data.ncl.28669472 . The Matlab code of the explored transformation can be found here: https://doi.org/10.25405/data.ncl.28669673.

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