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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...

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Main Authors:	Lim, Jia Zheng, James Mountstephens, Jason Teo
Format:	Article
Language:	English
Published:	MDPI 2020
Subjects:	QA75.5-76.95 Electronic computers. Computer science TK7885-7895 Computer engineering. Computer hardware
Online Access:	https://eprints.ums.edu.my/id/eprint/42470/1/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/42470/ http://dx.doi.org/10.3390/s20082384
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id	my.ums.eprints.42470
record_format	eprints
spelling	my.ums.eprints.424702024-12-31T01:21:48Z https://eprints.ums.edu.my/id/eprint/42470/ Emotion recognition using eye-tracking: taxonomy, review and current challenges Lim, Jia Zheng James Mountstephens Jason Teo QA75.5-76.95 Electronic computers. Computer science TK7885-7895 Computer engineering. Computer hardware 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 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/42470/1/FULL%20TEXT.pdf Lim, Jia Zheng and James Mountstephens and Jason Teo (2020) Emotion recognition using eye-tracking: taxonomy, review and current challenges. Sensors, 20. pp. 1-21. http://dx.doi.org/10.3390/s20082384
institution	Universiti Malaysia Sabah
building	UMS Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Sabah
content_source	UMS Institutional Repository
url_provider	http://eprints.ums.edu.my/
language	English
topic	QA75.5-76.95 Electronic computers. Computer science TK7885-7895 Computer engineering. Computer hardware
spellingShingle	QA75.5-76.95 Electronic computers. Computer science TK7885-7895 Computer engineering. Computer hardware Lim, Jia Zheng James Mountstephens Jason Teo Emotion recognition using eye-tracking: taxonomy, review and current challenges
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	Article
author	Lim, Jia Zheng James Mountstephens Jason Teo
author_facet	Lim, Jia Zheng James Mountstephens Jason Teo
author_sort	Lim, Jia Zheng
title	Emotion recognition using eye-tracking: taxonomy, review and current challenges
title_short	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_sort	emotion recognition using eye-tracking: taxonomy, review and current challenges
publisher	MDPI
publishDate	2020
url	https://eprints.ums.edu.my/id/eprint/42470/1/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/42470/ http://dx.doi.org/10.3390/s20082384
_version_	1821003221547614208
score	13.226497

Emotion recognition using eye-tracking: taxonomy, review and current challenges

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