A cost function to determine the optimum filter and parameters for stabilizing gaze data

A cost function to determine the optimum filter and parameters for stabilizing gaze data

Prior to delivery of data, eye tracker software may apply filtering to correct for noise. Although filtering produces much better precision of data, it may add to the time it takes for the reporting of gaze data to stabilise after a saccade due to the usage of a sliding window. The effect of variou...

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Bibliographic Details
Main Author: Pieter Blignaut
Format: Article
Language:English
Published: Bern Open Publishing 2019-07-01
Series:Journal of Eye Movement Research
Subjects:
Eye-tracking
Filters
Data quality
Accuracy
Precision
Latency
Online Access:https://bop.unibe.ch/JEMR/article/view/4487

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