Toward Multimodal Asynchronous Collaboration in VR Artistic Creation with S.P.A.R.K
Year: 2025
Type: conference-paper
Abstract: Recent artistic explorations in VR environments have explored how users engage with virtual spaces, sounds, and bodies whether, as artists, coders, or spectators. While many applications focus primarily on musical interaction or motion capture, few allow users to actively compose spatial and temporal relationships within a multimodal collaborative creation context merging altogether different artistic modalities. In this project, we present a Virtual Reality application that enables novel forms of collaboration between dancers and musicians. The application allows dancers to record full-body performances, which musicians can then use as the basis for sonic composition by spatially mapping sound triggers onto the dancer’s recorded movement. Rather than relying on live capture or real-time gesture tracking, our approach treats movement as a timeline for interaction blending choreography with sound design in an asynchronous workflow. We employ an iterative design process to ensure usability among experts. This paper details the first implementation and study involving 10 participants recruited from professional and amateur artists with electronic music backgrounds, highlighting positive reception of the application’s creative potential and usability.
Institutions: Centre National de la Recherche Scientifique, Institut national de recherche en sciences et technologies du numérique, Institut de Recherche en Informatique et Systèmes Aléatoires, Institut National des Sciences Appliquées de Rennes, Centre Inria de l'Université de Rennes, SEAMLESS: Interaction et collaboration fluides à travers le continuum réalité-virtualité, Université de Rennes, Université de Lille, Institut de Recherche sur les Composants logiciels et matériels pour l'Information et la Communication Avancée, Centre de Recherche en Informatique, Signal et Automatique de Lille
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Funder: Agence Nationale de la Recherche
OpenAlex ID: W4415035155
