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AR Cloud: Towards Collaborative Augmented Reality at a Large-Scale

Authors: Nam-Duong Duong; Christophe Cutullic; Jean-Marie Hénaff; Jérôme Royan;

AR Cloud: Towards Collaborative Augmented Reality at a Large-Scale

Abstract

Augmented Reality (AR) appears as one of the most promising technologies for the next decades with a lot of applications in Industry 4.0. Unfortunately, most of existing systems are limited to small environments and running on a single device. To cope with these limitations, we present in this paper an AR Cloud solution for real-time crowd mapping. We propose an AR cloud service architecture that is able to 1) continuously relocalize AR devices in relation to the reference coordinate system of a common global 3D map in order to estimate the initial pose of the AR device and to correct tracking drift as soon as possible; 2) locally map in 3D the real environment surrounding each AR device; 3) fuse these 3D local maps with the global 3D map in order to keep it up-to-date, mandatory feature when real environment changes over time. Finally, we show engexperiments of our AR cloud platform at a large scale.

Keywords

Augmented Reality, Map Update, Crowd- Mapping, Spatial Computing

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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