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How to choose the size of facial areas of interest in interactive eye tracking
Advances in eye tracking technology have enabled the development of interactive experimental setups to study social attention. Since these setups differ substantially from the eye tracker manufacturer’s test conditions, validation is essential with regard to the quality of gaze data and other factor...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8815978/ https://www.ncbi.nlm.nih.gov/pubmed/35120188 http://dx.doi.org/10.1371/journal.pone.0263594 |
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author | Vehlen, Antonia Standard, William Domes, Gregor |
author_facet | Vehlen, Antonia Standard, William Domes, Gregor |
author_sort | Vehlen, Antonia |
collection | PubMed |
description | Advances in eye tracking technology have enabled the development of interactive experimental setups to study social attention. Since these setups differ substantially from the eye tracker manufacturer’s test conditions, validation is essential with regard to the quality of gaze data and other factors potentially threatening the validity of this signal. In this study, we evaluated the impact of accuracy and areas of interest (AOIs) size on the classification of simulated gaze (fixation) data. We defined AOIs of different sizes using the Limited-Radius Voronoi-Tessellation (LRVT) method, and simulated gaze data for facial target points with varying accuracy. As hypothesized, we found that accuracy and AOI size had strong effects on gaze classification. In addition, these effects were not independent and differed in falsely classified gaze inside AOIs (Type I errors; false alarms) and falsely classified gaze outside the predefined AOIs (Type II errors; misses). Our results indicate that smaller AOIs generally minimize false classifications as long as accuracy is good enough. For studies with lower accuracy, Type II errors can still be compensated to some extent by using larger AOIs, but at the cost of more probable Type I errors. Proper estimation of accuracy is therefore essential for making informed decisions regarding the size of AOIs in eye tracking research. |
format | Online Article Text |
id | pubmed-8815978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-88159782022-02-05 How to choose the size of facial areas of interest in interactive eye tracking Vehlen, Antonia Standard, William Domes, Gregor PLoS One Research Article Advances in eye tracking technology have enabled the development of interactive experimental setups to study social attention. Since these setups differ substantially from the eye tracker manufacturer’s test conditions, validation is essential with regard to the quality of gaze data and other factors potentially threatening the validity of this signal. In this study, we evaluated the impact of accuracy and areas of interest (AOIs) size on the classification of simulated gaze (fixation) data. We defined AOIs of different sizes using the Limited-Radius Voronoi-Tessellation (LRVT) method, and simulated gaze data for facial target points with varying accuracy. As hypothesized, we found that accuracy and AOI size had strong effects on gaze classification. In addition, these effects were not independent and differed in falsely classified gaze inside AOIs (Type I errors; false alarms) and falsely classified gaze outside the predefined AOIs (Type II errors; misses). Our results indicate that smaller AOIs generally minimize false classifications as long as accuracy is good enough. For studies with lower accuracy, Type II errors can still be compensated to some extent by using larger AOIs, but at the cost of more probable Type I errors. Proper estimation of accuracy is therefore essential for making informed decisions regarding the size of AOIs in eye tracking research. Public Library of Science 2022-02-04 /pmc/articles/PMC8815978/ /pubmed/35120188 http://dx.doi.org/10.1371/journal.pone.0263594 Text en © 2022 Vehlen et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Vehlen, Antonia Standard, William Domes, Gregor How to choose the size of facial areas of interest in interactive eye tracking |
title | How to choose the size of facial areas of interest in interactive eye tracking |
title_full | How to choose the size of facial areas of interest in interactive eye tracking |
title_fullStr | How to choose the size of facial areas of interest in interactive eye tracking |
title_full_unstemmed | How to choose the size of facial areas of interest in interactive eye tracking |
title_short | How to choose the size of facial areas of interest in interactive eye tracking |
title_sort | how to choose the size of facial areas of interest in interactive eye tracking |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8815978/ https://www.ncbi.nlm.nih.gov/pubmed/35120188 http://dx.doi.org/10.1371/journal.pone.0263594 |
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