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abstract

Eye Tracking Emotion Evoking Interaction Based on Go/No-Go Paradigm VR Demonstration

Published: 13 January 2023 Publication History

Abstract

This demo proposes to evoke subjects’ emotions in a VR scene versus a computer screen scene and to test subjects’ attentional bias to emotional face stimuli after receiving emotion evoking of different potencies. The study will also collect data on the time from the appearance of the target stimulus in the eye-movement task to the time when subjects take their gaze away from the distracting stimulus (emotional face) and look at the target stimulus as an indicator of emotional intensity, and compare the difference in the intensity of emotion evoking at high and low immersion levels to investigate the effect of VR immersion experiences on emotion evoking at different levels of pleasure and different levels of arousal. The results of this study can be further applied to robot-assisted instructional design to help students obtain appropriate emotional states for maximum efficiency in learning.

Supplementary Material

MP4 File (VRCAI-39.mp4)
Presentation video - short version of [VR Demonstration of Eye Tracking Emotion Evoking Interaction Based on Go/No-Go Paradigm]

References

[1]
M.W. Becker and M. Leinenger. 2011. attentional selection is biased toward mood-congruent stimuli. emotion 11(2011), 1248–1254.
[2]
Feng Liu, Hanyang Wang, Xun Jia, Jiahao Zhang, Jingyi Hu, Siyuan Shen, Xiyi Wang, Ying Lei, Aimin Zhou, Jiayin Qi, and Zhibin Li. 2022a. OPO-FCM: A Computational Affection Based OCC-PAD-OCEAN Federation Cognitive Modeling Approach. IEEE Transactions on Computational Social Systems (2022), 1–13. https://doi.org/10.1109/TCSS.2022.3199119
[3]
Feng Liu, Hanyang Wang, Jiahao Zhang, Ziwang Fu, Aimin Zhou, Jiayin Qi, and Zhibin Li. 2022b. EvoGAN: An evolutionary computation assisted GAN. Neurocomputing 469(2022), 81–90. https://doi.org/10.1016/j.neucom.2021.10.060
[4]
Feng Liu, Yihao Zhou, Xun Jia, Hanyang Wang, Siyuan Shen, and Aimin Zhou. 2022c. High-arousal positive emotion evoking is more effective in VR than on a 2D monitor based on computational affection. In Proceedings of the 44th Annual Meeting of the Cognitive Science Society, CogSci (2022). 3779.
[5]
Aimin Zhou, Xiaozhe Yang, Wen Wu, Ningning Zhou, Feng Liu, and Liang He. 2021. Computational affection: A catalyst for human-centered education. Science374-Oct.1 App. TN.6563 (2021).

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Published In

cover image ACM Conferences
VRCAI '22: Proceedings of the 18th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry
December 2022
284 pages
ISBN:9798400700316
DOI:10.1145/3574131
  • Editors:
  • Enhua Wu,
  • Lionel Ming-Shuan Ni,
  • Zhigeng Pan,
  • Daniel Thalmann,
  • Ping Li,
  • Charlie C.L. Wang,
  • Lei Zhu,
  • Minghao Yang
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 January 2023

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Author Tags

  1. 360° videos
  2. Computational affection
  3. Emotion classification
  4. Emotion evoking
  5. Eye tracking
  6. Virtual Reality

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  • Refereed limited

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VRCAI '22
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Overall Acceptance Rate 51 of 107 submissions, 48%

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