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Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges
The ability to detect users’ emotions for the purpose of emotion engineering is currently one of the main endeavors of machine learning in affective computing. Among the more common approaches to emotion detection are methods that rely on electroencephalography (EEG), facial image processing and spe...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219342/ https://www.ncbi.nlm.nih.gov/pubmed/32331327 http://dx.doi.org/10.3390/s20082384 |
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author | Lim, Jia Zheng Mountstephens, James Teo, Jason |
author_facet | Lim, Jia Zheng Mountstephens, James Teo, Jason |
author_sort | Lim, Jia Zheng |
collection | PubMed |
description | The ability to detect users’ emotions for the purpose of emotion engineering is currently one of the main endeavors of machine learning in affective computing. Among the more common approaches to emotion detection are methods that rely on electroencephalography (EEG), facial image processing and speech inflections. Although eye-tracking is fast in becoming one of the most commonly used sensor modalities in affective computing, it is still a relatively new approach for emotion detection, especially when it is used exclusively. In this survey paper, we present a review on emotion recognition using eye-tracking technology, including a brief introductory background on emotion modeling, eye-tracking devices and approaches, emotion stimulation methods, the emotional-relevant features extractable from eye-tracking data, and most importantly, a categorical summary and taxonomy of the current literature which relates to emotion recognition using eye-tracking. This review concludes with a discussion on the current open research problems and prospective future research directions that will be beneficial for expanding the body of knowledge in emotion detection using eye-tracking as the primary sensor modality. |
format | Online Article Text |
id | pubmed-7219342 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72193422020-05-22 Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges Lim, Jia Zheng Mountstephens, James Teo, Jason Sensors (Basel) Review The ability to detect users’ emotions for the purpose of emotion engineering is currently one of the main endeavors of machine learning in affective computing. Among the more common approaches to emotion detection are methods that rely on electroencephalography (EEG), facial image processing and speech inflections. Although eye-tracking is fast in becoming one of the most commonly used sensor modalities in affective computing, it is still a relatively new approach for emotion detection, especially when it is used exclusively. In this survey paper, we present a review on emotion recognition using eye-tracking technology, including a brief introductory background on emotion modeling, eye-tracking devices and approaches, emotion stimulation methods, the emotional-relevant features extractable from eye-tracking data, and most importantly, a categorical summary and taxonomy of the current literature which relates to emotion recognition using eye-tracking. This review concludes with a discussion on the current open research problems and prospective future research directions that will be beneficial for expanding the body of knowledge in emotion detection using eye-tracking as the primary sensor modality. MDPI 2020-04-22 /pmc/articles/PMC7219342/ /pubmed/32331327 http://dx.doi.org/10.3390/s20082384 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Lim, Jia Zheng Mountstephens, James Teo, Jason Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges |
title | Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges |
title_full | Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges |
title_fullStr | Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges |
title_full_unstemmed | Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges |
title_short | Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges |
title_sort | emotion recognition using eye-tracking: taxonomy, review and current challenges |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7219342/ https://www.ncbi.nlm.nih.gov/pubmed/32331327 http://dx.doi.org/10.3390/s20082384 |
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