SceneCam: Using AR to improve multi-camera remote collaboration

Rasmussen, TA; Huang, W

SceneCam: Using AR to improve multi-camera remote collaboration

Rasmussen, TA Huang, W

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Publisher:: ACM Press
Publication Type:: Conference Proceeding
Citation:: SIGGRAPH Asia 2019 XR, SA 2019, 2019, pp. 36-37
Issue Date:: 2019-11-17

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Field	Value	Language
dc.contributor.author	Rasmussen, TA
dc.contributor.author	Huang, W https://orcid.org/0000-0002-5190-7839
dc.date	2019-11-17
dc.date.accessioned	2020-05-29T22:03:43Z
dc.date.available	2020-05-29T22:03:43Z
dc.date.issued	2019-11-17
dc.identifier.citation	SIGGRAPH Asia 2019 XR, SA 2019, 2019, pp. 36-37
dc.identifier.isbn	9781450369473
dc.identifier.uri	http://hdl.handle.net/10453/140997
dc.description.abstract	© 2019 Association for Computing Machinery. During multi-camera remote collaboration on physical tasks, as the name implies, multiple cameras capture different areas and perspectives of a task space. It can be challenging for the remote user to obtain the right view of the local user and to understand the spatial relationship between the disjointed views of task space areas. We present SceneCam, a prototype with which we use AR to explore different techniques for improving multi-camera remote collaboration by making optimal camera selection easier and faster for the remote user and by making the spatial relationship between task space areas explicit. To this end, SceneCam implements two camera selection techniques: nudging the remote user to select an optimal camera view of the local user, and automatic selection of an optimal camera view of the local user. Furthermore, SceneCam provides the remote user with two focus-in-context views - exocentric and egocentric views - that visualize the spatial relationship between the multiple task space areas and the local user.
dc.language	en
dc.publisher	ACM Press
dc.relation.ispartof	SIGGRAPH Asia 2019 XR, SA 2019
dc.relation.ispartof	SIGGRAPH Asia 2019 XR
dc.relation.isbasedon	10.1145/3355355.3361892
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	SceneCam: Using AR to improve multi-camera remote collaboration
dc.type	Conference Proceeding
pubs.organisational-group	/University of Technology Sydney/Faculty of Transdisciplinary Innovation
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2020-05-29T22:03:38Z
pubs.finish-date	2019-11-20
pubs.publication-status	Published
pubs.start-date	2019-11-17
utslib.start-page	36

Abstract:

© 2019 Association for Computing Machinery. During multi-camera remote collaboration on physical tasks, as the name implies, multiple cameras capture different areas and perspectives of a task space. It can be challenging for the remote user to obtain the right view of the local user and to understand the spatial relationship between the disjointed views of task space areas. We present SceneCam, a prototype with which we use AR to explore different techniques for improving multi-camera remote collaboration by making optimal camera selection easier and faster for the remote user and by making the spatial relationship between task space areas explicit. To this end, SceneCam implements two camera selection techniques: nudging the remote user to select an optimal camera view of the local user, and automatic selection of an optimal camera view of the local user. Furthermore, SceneCam provides the remote user with two focus-in-context views - exocentric and egocentric views - that visualize the spatial relationship between the multiple task space areas and the local user.

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http://hdl.handle.net/10453/140997