ArticleJournal of eye movement research2023
Testing different function fitting methods for mobile eye-tracker calibration.
Article in Journal of eye movement research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
During calibration, an eye-tracker fits a mapping function from features to a target gaze point. While there is research on which mapping function to use, little is known about how to best estimate the function's parameters. We investigate how different fitting methods impact accuracy under different noise factors, such as mobile eye-tracker imprecision or detection errors in feature extraction during calibration. For this purpose, a simulation of binocular gaze was developed for a) different calibration patterns and b) different noise characteristics. We found the commonly used polynomial regression via least-squares-error fit often lacks to find good mapping functions when compared to ridge regression. Especially as data becomes noisier, outlier-tolerant fitting methods are of importance. We demonstrate a reduction in mean MSE of 20% by simply using ridge over polynomial fit in a mobile eye-tracking experiment.
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