Becoming An Animal? Exploring Proteus Effect Based on Human-avatar Hand Gesture Consistency
Human cognition and behavior can be unconsciously affected by personal avatars in the virtual world, a phenomenon known as the Proteus Effect. When using first-person non-human avatars, the characteristics of virtual hands may also induce relevant cognitive and even behavioral patterns in real human hands. Therefore, evaluating human-avatar gesture consistency may be a potentially effective method for objectively assessing the Proteus Effect when using non-human avatars. To explore this question, we first created human and non-human avatars, including three animals. Then, we constructed a dataset of hand gestures and trained a model to dynamically recognize real-hand gestures that were consistent with corresponding avatar hands. Next, we designed a virtual reality experimental task involving grasping objects with intuitive gestures and performed a 2 (avatar type: human/non-human) $* 2$ (virtual hand: presence/absence of spontaneous movement) within-subject experiment to examine the effects of avatar characteristics on self-illusion and human-avatar gesture consistency. The results showed that participants performed a significantly larger percentage of gestures that were consistent with their currently used avatars. Additionally, participants did experience self-illusion when using non-human avatars, although the levels were significantly lower than those when using human avatars. Therefore, self-illusion may serve as a perceptual antecedent of the Proteus Effect, even with non-human avatars, inadvertently altering the behavioral gestures of their real hands. In conclusion, detecting human-avatar gesture consistency can help evaluate the Proteus Effect.
Authors
- Ying Lin (ORCID: https://orcid.org/0000-0002-2270-272X)
- Yulong Bian (ORCID: https://orcid.org/0000-0003-0999-0656)
- Tangjun Qu
- Junjie Wang (ORCID: https://orcid.org/0000-0002-3397-2813)
- Juan Liu (ORCID: https://orcid.org/0000-0003-1069-2875)
- Chao Zhou (ORCID: https://orcid.org/0000-0002-0753-7500)
- Kaiyuan Jiang (ORCID: https://orcid.org/0000-0002-6155-2613)
- Baiqiao Zhang (ORCID: https://orcid.org/0009-0009-7856-5072)
Institutions
- Shandong University (CN)
- Institute of Software (CN)
Publication Details
- Published
- 2024-10-21
- DOI
- https://doi.org/10.1109/ismar62088.2024.00093
- Citations
- 2
- Primary Topic
- Hand Gesture Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.74
Funders
- Shandong University
- Ministry of Education