
Slide

Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Chartier, S.; Renaud, P.
An online noise filter for eye-tracker data recorded in a virtual environment Article d'actes
Dans: Eye Tracking Research and Applications Symposium (ETRA), p. 153–156, Savannah, GA, 2008, ISBN: 978-159593982-1 (ISBN), (Journal Abbreviation: Eye Track. Res. Appl. Symp. (ETRA)).
Résumé | Liens | BibTeX | Étiquettes: Average filter, Eye trackers, Eye-blinks, Eye-tracker, Eye-tracker data, Noise filters, Noise removal, Noisy data, Off-line filters, Online filtering, Virtual environments, virtual reality
@inproceedings{chartier_online_2008,
title = {An online noise filter for eye-tracker data recorded in a virtual environment},
author = {S. Chartier and P. Renaud},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77950329450&doi=10.1145%2f1344471.1344511&partnerID=40&md5=7ba397a215e76c9d511800ccb267b5cd},
doi = {10.1145/1344471.1344511},
isbn = {978-159593982-1 (ISBN)},
year = {2008},
date = {2008-01-01},
booktitle = {Eye Tracking Research and Applications Symposium (ETRA)},
pages = {153–156},
address = {Savannah, GA},
abstract = {A Recursive Online Weight Average filter (ROWA) is proposed to remove and replace noisy data obtained from eye tracker. Since the filter can be implemented online, it can detect and replace noisy data using solely past records. Simulations results indicate that the filter achieved the same performance compared to other standard offline filters while being simpler. Copyright © 2008 by the Association for Computing Machinery, Inc.},
note = {Journal Abbreviation: Eye Track. Res. Appl. Symp. (ETRA)},
keywords = {Average filter, Eye trackers, Eye-blinks, Eye-tracker, Eye-tracker data, Noise filters, Noise removal, Noisy data, Off-line filters, Online filtering, Virtual environments, virtual reality},
pubstate = {published},
tppubtype = {inproceedings}
}
A Recursive Online Weight Average filter (ROWA) is proposed to remove and replace noisy data obtained from eye tracker. Since the filter can be implemented online, it can detect and replace noisy data using solely past records. Simulations results indicate that the filter achieved the same performance compared to other standard offline filters while being simpler. Copyright © 2008 by the Association for Computing Machinery, Inc.