Affecting Audience Valence and Arousal in 360 Immersive Environments : How Powerful Neural Style Transfer Is?
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Title of host publication | Virtual, Augmented and Mixed Reality |
Subtitle of host publication | 16th International Conference, VAMR 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Washington, DC, USA, June 29 – July 4, 2024, Proceedings, Part I |
Editors | Jessie Y. C. Chen, Gino Fragomeni |
Place of Publication | Cham |
Publisher | Springer |
Pages | 224-243 |
ISBN (electronic) | 978-3-031-61041-7 |
ISBN (print) | 978-3-031-61040-0 |
Publication status | Published - 2024 |
Publication series
Name | Lecture Notes in Computer Science |
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Volume | 14706 |
ISSN (Print) | 0302-9743 |
ISSN (electronic) | 1611-3349 |
Conference
Title | 16th International Conference on Virtual, Augmented and Mixed Reality (VAMR 2024), held as part of the 26th International Conference on Human-Computer Interaction, HCI International 2024 (HCII 2024) |
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Location | Hybrid |
Place | United States |
City | Washington |
Period | 29 June - 4 July 2024 |
Link(s)
Abstract
Immersive experiences in Virtual Reality (VR) platforms often require customized content that can be adapted to in-game situations and specific player actions that lead to individualized effects. Controlling the positive-negative emotional valence and the level of arousal of the immersive content allows VR systems to provide situation-specific and action-specific affective influence on players, giving them an experience that is tailor-made for the narrative and interaction espoused by the system. To generate different emotional influences for the same content, we created a system that uses Neural Style Transfer (NST) along with a set of style images with known affective ratings to procedurally generate different versions of the same 360 environments in VR with differing affective influences for players. To explore how the NST-generated VR affects participants’ affective perception, we conducted two user studies (N=30 and N=28). Users experienced four separate VR environments with different affective ratings. After each experience, we performed a survey to evaluate their affection, including Emotional Matching Tasks and interviews. Findings suggested that users are more likely to be aware of arousal differences than valence differences, which are mainly perceived by the degree of contrast between color and content of the environment. The stylized features gained from NST that affect the perception of valence are the color tone, the clarity of the texture, and the familiarity of the content for the user. Our work contributes novel insight into how users respond to generated VR environments and provides a machine-learning-based strategy for constructing an immersive environment to influence the affective experience of users, without altering any content and the game mechanism. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Research Area(s)
- 360 Image Generation, Affective Experience, Affective VR, Human-computer Interaction, Neural Style Transfer
Bibliographic Note
Research Unit(s) information for this publication is provided by the author(s) concerned.
Citation Format(s)
Affecting Audience Valence and Arousal in 360 Immersive Environments: How Powerful Neural Style Transfer Is? / Li, Yanheng; Bai, Long; Mao, Yaxuan et al.
Virtual, Augmented and Mixed Reality: 16th International Conference, VAMR 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Washington, DC, USA, June 29 – July 4, 2024, Proceedings, Part I. ed. / Jessie Y. C. Chen; Gino Fragomeni. Cham: Springer, 2024. p. 224-243 (Lecture Notes in Computer Science; Vol. 14706).
Virtual, Augmented and Mixed Reality: 16th International Conference, VAMR 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Washington, DC, USA, June 29 – July 4, 2024, Proceedings, Part I. ed. / Jessie Y. C. Chen; Gino Fragomeni. Cham: Springer, 2024. p. 224-243 (Lecture Notes in Computer Science; Vol. 14706).
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review