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Title: GazeMetrics: An Open-Source Tool for Measuring the Data Quality of HMD-based Eye Trackers
As virtual reality (VR) garners more attention for eye tracking research, knowledge of accuracy and precision of head-mounted display (HMD) based eye trackers becomes increasingly necessary. It is tempting to rely on manufacturer-provided information about the accuracy and precision of an eye tracker. However, unless data is collected under ideal conditions, these values seldom align with on-site metrics. Therefore, best practices dictate that accuracy and precision should be measured and reported for each study. To address this issue, we provide a novel open-source suite for rigorously measuring accuracy and precision for use with a variety of HMD-based eye trackers. This tool is customizable without having to alter the source code, but changes to the code allow for further alteration. The outputs are available in real time and easy to interpret, making eye tracking with VR more approachable for all users.
Authors:
; ; ;
Award ID(s):
1911041
Publication Date:
NSF-PAR ID:
10193015
Journal Name:
ACM symposium on Eye Tracking Research and Applications
Volume:
19
Page Range or eLocation-ID:
1 to 5
Sponsoring Org:
National Science Foundation
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