Abstract
For eye tracking to become a ubiquitous part of our everyday interaction with computers, we first need to understand its limitations outside rigorously controlled labs, and develop robust applications that can be used by a broad range of users and in various environments. Toward this end, we collected eye tracking data from 80 people in a calibration-style task, using two different trackers in two lighting conditions. We found that accuracy and precision can vary between users and targets more than six-fold, and report on differences between lighting, trackers, and screen regions. We show how such data can be used to determine appropriate target sizes and to optimize the parameters of commonly used filters. We conclude with design recommendations and examples how our findings and methodology can inform the design of error-aware adaptive applications.
Links
- https://www.slideshare.net/AnnaMariaFeit/toward-everyday-gaze-input-accuracy-and[...]
- doi:10.1145/3025453.3025599
BibTeX (Download)
@inproceedings{Feit2017,
title = {Toward everyday gaze input: Accuracy and precision of eye tracking and implications for design},
author = {Anna Maria Feit and Shane Williams and Arturo Toledo and Ann Paradiso and Harish Kulkarni and Shaun Kane and Meredith Ringel Morris},
url = {https://www.slideshare.net/AnnaMariaFeit/toward-everyday-gaze-input-accuracy-and-precision-of-eye-tracking-and-implications-for-design},
doi = {10.1145/3025453.3025599},
isbn = {9781450346559},
year = {2017},
date = {2017-05-01},
urldate = {2017-05-01},
booktitle = {SIGCHI Conference on Human Factors in Computing Systems},
publisher = {ACM},
address = {New York, NY, USA},
abstract = {For eye tracking to become a ubiquitous part of our everyday interaction with computers, we first need to understand its limitations outside rigorously controlled labs, and develop robust applications that can be used by a broad range of users and in various environments. Toward this end, we collected eye tracking data from 80 people in a calibration-style task, using two different trackers in two lighting conditions. We found that accuracy and precision can vary between users and targets more than six-fold, and report on differences between lighting, trackers, and screen regions. We show how such data can be used to determine appropriate target sizes and to optimize the parameters of commonly used filters. We conclude with design recommendations and examples how our findings and methodology can inform the design of error-aware adaptive applications.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}