Collaborative Work in Augmented Reality: A Survey - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles IEEE Transactions on Visualization and Computer Graphics Year : 2022

Collaborative Work in Augmented Reality: A Survey

Mickael Sereno
Xiyao Wang
Lonni Besançon
Tobias Isenberg

Abstract

In Augmented Reality (AR), users perceive virtual content anchored in the real world. It is used in medicine, education, games, navigation, maintenance, product design, and visualization, in both single-user and multiuser scenarios. Multiuser AR has received limited attention from researchers, even though AR has been in development for more than two decades. We present the state of existing work at the intersection of AR and Computer-Supported Collaborative Work (AR-CSCW), by combining a systematic survey approach with an exploratory, opportunistic literature search. We categorize 65 papers along the dimensions of space, time, role symmetry (whether the roles of users are symmetric), technology symmetry (whether the hardware platforms of users are symmetric), and output and input modalities. We derive design considerations for collaborative AR environments, and identify under-explored research topics. These include the use of heterogeneous hardware considerations and 3D data exploration research areas. This survey is useful for newcomers to the field, readers interested in an overview of CSCW in AR applications, and domain experts seeking up-to-date information.
Fichier principal
Vignette du fichier
Sereno_2021_CWA.pdf (6.36 Mo) Télécharger le fichier
Vignette du fichier
paperimage.png (47.01 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Format : Figure, Image
Loading...

Dates and versions

hal-02971697 , version 1 (19-10-2020)

Identifiers

Cite

Mickael Sereno, Xiyao Wang, Lonni Besançon, Michael J Mcguffin, Tobias Isenberg. Collaborative Work in Augmented Reality: A Survey. IEEE Transactions on Visualization and Computer Graphics, 2022, 28 (6), pp.2530-2549. ⟨10.1109/TVCG.2020.3032761⟩. ⟨hal-02971697⟩
594 View
808 Download

Altmetric

Share

Gmail Facebook X LinkedIn More