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Assessing Binocular Central Visual Field and Binocular Eye Movements in a Dichoptic Viewing Condition

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Angular Offset Distributions During Fixation Are, More Often Than Not, Multimodal.

Lee Friedman¹, Dillon Lohr¹, Timothy Hanson²

¹Texas State University, San Marcos, Texas, USA.

Journal of Eye Movement Research

|June 14, 2021

Summary

This summary is machine-generated.

Eye-tracking accuracy measurements are often misleading due to multimodal error distributions. This study reveals most distributions are multimodal, necessitating new accuracy assessment methods beyond simple means.

Keywords:

Eye movement accuracy drift eye tracking fixation gaze microsaccades multimodality

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Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity

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Published on: March 18, 2019

Area of Science:

Human-Computer Interaction
Ophthalmology
Cognitive Science

Background:

Eye-tracking accuracy is typically measured by angular offset, assuming normal distribution.
The mean angular offset is a common metric for eye-tracking accuracy.
Current methods may misinterpret accuracy when error distributions are not unimodal and normal.

Purpose of the Study:

To investigate the distribution of eye-tracking position errors.
To challenge the assumption of unimodal and normal error distributions in eye-tracking.
To propose alternative methods for measuring eye-tracking accuracy with multimodal distributions.

Main Methods:

Analysis of fixation angular offset distributions from eye-tracking data.
Statistical evaluation of distribution unimodality and normality.
Exploration of fixation drift as a factor in multimodality.

Main Results:

The majority of fixation angular offset distributions were found to be multimodal.
Only a small percentage (1.7%) of distributions were both unimodal and normal.
Multimodality was observed even with single, continuous fixation segments.

Conclusions:

The mean angular offset is often an inadequate measure of eye-tracking accuracy.
New approaches are needed to accurately assess eye-tracking performance with multimodal error distributions.
Fixation drift may contribute to the observed multimodality in eye-tracking errors.