Eye Tracking Calibration based on Smooth Pursuit with Regulated Visual Guidance

Yangyang Li, Yangyang Li, Lili Guo, Guangbin Sun, Rongrong Fu, Zhen Yan, Ji Liang

2022

Abstract

Eye tracking calibration based on smooth pursuit has the characteristics of rapidity and convenience, but most smooth pursuit calibration methods are based on spontaneous and passive gazes. The spatial-temporal characteristics of the target movement can significantly affect the tracking performance, but few works have performed calibration considering the effects of both the spatial and temporal variance of the smooth pursuit target. Therefore, we proposed an off-line smoothing pursuit calibration featuring actively regulated speed under specially designed visual guidance paths. In our prelude experiments, we found that there was an obvious correlation between the eye movement velocity and the error of gaze point measurement. In particular, when the movement velocity of gaze exceeded 6°/s, the accuracy and precision of the eye-tracking system were obviously lower. Based on these findings, the visual guidance trajectory was regulated, with the speed kept below 6°/s. The smooth pursuit calibration was combined with the neural network learning method. The results showed that the mean absolute error was reduced from 1.0° to 0.4°, and the full calibration process took only approximately 45 seconds.

Paper Citation

in Harvard Style

Li Y., Guo L., Sun G., Fu R., Yan Z. and Liang J. (2022). Eye Tracking Calibration based on Smooth Pursuit with Regulated Visual Guidance. In Proceedings of the 14th International Joint Conference on Computational Intelligence - Volume 1: ROBOVIS; ISBN 978-989-758-611-8, SciTePress, pages 417-425. DOI: 10.5220/0011524900003332

in Bibtex Style

@conference{robovis22,
author={Yangyang Li and Lili Guo and Guangbin Sun and Rongrong Fu and Zhen Yan and Ji Liang},
title={Eye Tracking Calibration based on Smooth Pursuit with Regulated Visual Guidance},
booktitle={Proceedings of the 14th International Joint Conference on Computational Intelligence - Volume 1: ROBOVIS},
year={2022},
pages={417-425},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011524900003332},
isbn={978-989-758-611-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computational Intelligence - Volume 1: ROBOVIS
TI - Eye Tracking Calibration based on Smooth Pursuit with Regulated Visual Guidance
SN - 978-989-758-611-8
AU - Li Y.
AU - Guo L.
AU - Sun G.
AU - Fu R.
AU - Yan Z.
AU - Liang J.
PY - 2022
SP - 417
EP - 425
DO - 10.5220/0011524900003332
PB - SciTePress