A Research Platform for Studying Mixed-Presence Collaboration

In this paper, we present a research platform to support studying collaboration in hybrid and co-located scenarios. Mixed-presence collaboration includes various novel and exciting use cases, such as situated and immersive data analysis by multiple users. However, research in this emerging field is hindered by the technical complexity of the setups and often requires re-implementation of common features. We address this issue by contributing a toolkit and research platform for mixed-presence collaboration that serves as an extensible baseline implementation and enables fast prototyping for user studies in collaborative mixed reality. Furthermore, our platform provides adjustable parameters, such as types of avatars, audio source placement, or the amount of simulated network latency. This way, developers are supported in making design choices regarding typical, re-occurring technical challenges.

Authors

Institutions

Publication Details

Published
2024-10-21
DOI
https://doi.org/10.1109/ismar-adjunct64951.2024.00058
Citations
1
Primary Topic
Team Dynamics and Performance
Type
article
Field-Weighted Citation Impact
0.64
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Research Platform for Studying Mixed-Presence Collaboration

Stefan Gumhold, Wolfgang Büschel, Marc Satkowski, Raimund Dachselt et al.
1 citations
Team Dynamics and Performance
0.64
article

A Research Platform for Studying Mixed-Presence Collaboration

Stefan Gumhold, Wolfgang Büschel, Marc Satkowski, Raimund Dachselt, Katja Krug
article en
1 citations

Abstract

In this paper, we present a research platform to support studying collaboration in hybrid and co-located scenarios. Mixed-presence collaboration includes various novel and exciting use cases, such as situated and immersive data analysis by multiple users. However, research in this emerging field is hindered by the technical complexity of the setups and often requires re-implementation of common features. We address this issue by contributing a toolkit and research platform for mixed-presence collaboration that serves as an extensible baseline implementation and enables fast prototyping for user studies in collaborative mixed reality. Furthermore, our platform provides adjustable parameters, such as types of avatars, audio source placement, or the amount of simulated network latency. This way, developers are supported in making design choices regarding typical, re-occurring technical challenges.

Technische Universität Dresden (DE)
Openalex Percentile: Top 25%
Team Dynamics and Performance
0.64
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.