Paper
28 April 2023 Improving conditions for recording human gaze data
Mingjie Gao, Jan Drewes
Author Affiliations +
Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 1261036 (2023) https://doi.org/10.1117/12.2671184
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China
Abstract
In artificial intelligence, machines first need to be trained before they can work. Most of the time, they are trained on human data, such as human-made labels, or human physiological data. Data quality from humans becomes an important factor for machine learning. In the field of machine vision, machines usually learn human intentions through human gaze data, which is typically collected using video-based eye movement recording devices. Gaze recording accuracy can vary with pupil size, pupil size can be manipulated by screen background luminance. Looking at the variability of pupil size over various luminance levels may provide insight into possible ways to improve data quality. Aiming at improving the quality from human gaze data, we measured human pupil size changes during gaze at different luminance levels using a video-based eye tracker. Results show that mean pupil size gradually decreases, but is most variable at medium luminance levels, the maximum coefficient of variation difference reaches 7.5%. Therefore, gaze data accuracy may be improved if recorded at low or high luminance levels.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mingjie Gao and Jan Drewes "Improving conditions for recording human gaze data", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 1261036 (28 April 2023); https://doi.org/10.1117/12.2671184
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KEYWORDS
Displays

Eye tracking

Eye

Machine learning

Education and training

Machine vision

Visualization

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