A comparative investigation of eye fixation-based 4-class emotion recognition in virtual reality using machine learning

Lim Jia Zheng and James Mountstephens and Jason Teo (2021) A comparative investigation of eye fixation-based 4-class emotion recognition in virtual reality using machine learning.

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Official URL: https://ieeexplore.ieee.org/abstract/document/9530...

Abstract

Research on emotion recognition that relies purely on eye-tracking data is very limited although the usability of eye-tracking technology has great potential for emotional recognition. This paper proposes a novel approach for 4-class emotion classification using eye-tracking data solely in virtual reality (VR) with machine learning algorithms. We classify emotions into four specific classes using VR stimulus. Eye fixation data was used as the emotional-relevant feature in this investigation. A presentation of 360 0 videos, which contains four different sessions, was played in VR to evoke the user’s emotions. The eye-tracking data was collected and recorded using an add-on eye-tracker in the VR headset. Three classifiers were used in the experiment, which are k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM). The findings showed that RF has the best performance among the classifiers, and achieved the highest accuracy of 80.55%.

Item Type:	Proceedings
Keyword:	Emotion recognition , Eye-tracking , Fixation , Machine learning , virtual reality
Subjects:	B Philosophy. Psychology. Religion > BF Psychology > BF1-990 Psychology Q Science > Q Science (General) > Q1-390 Science (General) > Q300-390 Cybernetics
Department:	FACULTY > Faculty of Computing and Informatics
Depositing User:	DG MASNIAH AHMAD -
Date Deposited:	03 May 2022 21:37
Last Modified:	03 May 2022 21:37
URI:	https://eprints.ums.edu.my/id/eprint/32528

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