EasyEyes: Crowded Dynamic Fixation for Online Psychophysics

Area of Science:

• Ophthalmology
• Computer Vision
• Human-Computer Interaction

Background:

• Online vision testing offers efficient data collection but requires precise gaze tracking.
• Traditional webcam-based gaze tracking lacks sufficient accuracy for online studies.
• Existing dynamic fixation tasks reduce, but do not eliminate, fixation errors.

Purpose of the Study:

• To introduce and evaluate a novel 'crowded dynamic fixation' task for enhancing gaze accuracy in online vision testing.
• To assess the effectiveness of crowding in further improving fixation compared to previous methods.
• To determine if crowded dynamic fixation can eliminate peeking behavior during peripheral threshold measurements.

Main Methods:

• Developed a 'crowded dynamic fixation' task incorporating visual clutter around a moving target.
• Assessed fixation accuracy by measuring RMS gaze error and peeking frequency during peripheral threshold measurements.
• Compared the crowded dynamic fixation task against stationary and dynamic fixation tasks.

Main Results:

• Crowded dynamic fixation reduced RMS gaze error by 47% compared to stationary fixation.
• Peeking occurred in 0% of trials with crowded dynamic fixation, versus 4% for dynamic and 9% for stationary fixation.
• The method eliminated implausibly low peripheral thresholds, suggesting improved fixation accuracy.

Conclusions:

• Crowded dynamic fixation provides accurate gaze control for online vision testing.
• This method effectively leverages crowding to minimize fixation errors and peeking.
• The technique holds promise for improving the reliability of remote vision assessment tools.