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A Conceptual Model and Taxonomy for Collaborative Augmented Reality.

Authors :
Marques B
Silva S
Alves J
Araujo T
Dias P
Santos BS
Source :
IEEE transactions on visualization and computer graphics [IEEE Trans Vis Comput Graph] 2022 Dec; Vol. 28 (12), pp. 5113-5133. Date of Electronic Publication: 2022 Oct 26.
Publication Year :
2022

Abstract

To support the nuances of collaborative work, many researchers have been exploring the field of Augmented Reality (AR), aiming to assist in co-located or remote scenarios. Solutions using AR allow taking advantage from seamless integration of virtual objects and real-world objects, thus providing collaborators with a shared understanding or common ground environment. However, most of the research efforts, so far, have been devoted to experiment with technology and mature methods to support its design and development. Therefore, it is now time to understand where the field stands and how well can it address collaborative work with AR, to better characterize and evaluate the collaboration process. In this article, we perform an analysis of the different dimensions that should be taken into account when analysing the contributions of AR to the collaborative work effort. Then, we bring these dimensions forward into a conceptual framework and propose an extended human-centered taxonomy for the categorization of the main features of Collaborative AR. Our goal is to foster harmonization of perspectives for the field, which may help create a common ground for systematization and discussion. We hope to influence and improve how research in this field is reported by providing a structured list of the defining characteristics. Finally, some examples of the use of the taxonomy are presented to show how it can serve to gather information for characterizing AR-supported collaborative work, and illustrate its potential as the grounds to elicit further studies.

Details

Language :
English
ISSN :
1941-0506
Volume :
28
Issue :
12
Database :
MEDLINE
Journal :
IEEE transactions on visualization and computer graphics
Publication Type :
Academic Journal
Accession number :
34347599
Full Text :
https://doi.org/10.1109/TVCG.2021.3101545