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Not Alone Here?! Scalability and User Experience of Embodied Ambient Crowds in Distributed Social Virtual Reality.

Authors :
Latoschik ME
Kern F
Stauffert JP
Bartl A
Botsch M
Lugrin JL
Source :
IEEE transactions on visualization and computer graphics [IEEE Trans Vis Comput Graph] 2019 May; Vol. 25 (5), pp. 2134-2144. Date of Electronic Publication: 2019 Feb 18.
Publication Year :
2019

Abstract

This article investigates performance and user experience in Social Virtual Reality (SVR) targeting distributed, embodied, and immersive, face-to-face encounters. We demonstrate the close relationship between scalability, reproduction accuracy, and the resulting performance characteristics, as well as the impact of these characteristics on users co-located with larger groups of embodied virtual others. System scalability provides a variable number of co-located avatars and Al-controlled agents with a variety of different appearances, including realistic-looking virtual humans generated from photogrammetry scans. The article reports on how to meet the requirements of embodied SVR with today's technical off-the-shelf solutions and what to expect regarding features, performance, and potential limitations. Special care has been taken to achieve low latencies and sufficient frame rates necessary for reliable communication of embodied social signals. We propose a hybrid evaluation approach which coherently relates results from technical benchmarks to subjective ratings and which confirms required performance characteristics for the target scenario of larger distributed groups. A user-study reveals positive effects of an increasing number of co-located social companions on the quality of experience of virtual worlds, i.e., on presence, possibility of interaction, and co-presence. It also shows that variety in avatar/agent appearance might increase eeriness but might also stimulate an increased interest of participants about the environment.

Details

Language :
English
ISSN :
1941-0506
Volume :
25
Issue :
5
Database :
MEDLINE
Journal :
IEEE transactions on visualization and computer graphics
Publication Type :
Academic Journal
Accession number :
30794185
Full Text :
https://doi.org/10.1109/TVCG.2019.2899250