Modeling Audience NPC's Diversity for Enhanced Illusionary Sociality in Collective VR Concert Experiences
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Date
2025
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Virtual reality (VR) live performances offer a novel style of experience through the deployment of three-dimensional cartoonlike performers and through spatiotemporally asynchronous participation. However, such experiences often lack the presence and atmospheric richness of physical live concerts. To address this gap, prior research has proposed audience non-player characters (NPCs) that emulate the collective characteristics of real-world audiences to enhance viewer engagement. In this study, we extend existing approaches by incorporating individual motion diversity to synthesize audience NPCs that form a heterogeneous and lifelike crowd. In addition to collective characteristics, such as music-driven motion changes and gradual synchronization, our modeling approach introduces agent-level diversity, even within the same motion categories. To assess the psychological impact of the proposed method, we developed a VR concert scenario featuring approximately 1,500 audience NPCs and conducted an empirical evaluation of the user experience. The findings indicate that enhanced motion heterogeneity can increase a viewer's sense of presence, engagement, perceived unity, and co-existence in a VR concert environment.
Description
CCS Concepts: Computing methodologies → Crowd simulation; Human-centered computing → Virtual reality; Entertainment computing
@inproceedings{10.2312:egve.20251343,
booktitle = {ICAT-EGVE 2025 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments},
editor = {Jorge, Joaquim A. and Sakata, Nobuchika},
title = {{Modeling Audience NPC's Diversity for Enhanced Illusionary Sociality in Collective VR Concert Experiences}},
author = {Ishinuki, Takehiro and Fujishiro, Issei},
year = {2025},
publisher = {The Eurographics Association},
ISSN = {1727-530X},
ISBN = {978-3-03868-278-3},
DOI = {10.2312/egve.20251343}
}