eCAR: edge-assisted Collaborative Augmented Reality Framework
Jinwoo Jeon, Woontack Woo

TL;DR
eCAR is an edge-assisted framework that enhances multi-user collaborative augmented reality by reducing network traffic and latency, ensuring consistent virtual object synchronization in large indoor environments.
Contribution
It introduces an innovative edge computing approach that maintains spatial-temporal consistency and reduces communication overhead in collaborative AR applications.
Findings
Reduced network traffic for coordinate system alignment.
Lower latency in virtual object synchronization.
Improved virtual object consistency across devices.
Abstract
We propose a novel edge-assisted multi-user collaborative augmented reality framework in a large indoor environment. In Collaborative Augmented Reality, data communication that synchronizes virtual objects has large network traffic and high network latency. Due to drift, CAR applications without continuous data communication for coordinate system alignment have virtual object inconsistency. In addition, synchronization messages for online virtual object updates have high latency as the number of collaborative devices increases. To solve this problem, we implement the CAR framework, called eCAR, which utilizes edge computing to continuously match the device's coordinate system with less network traffic. Furthermore, we extend the co-visibility graph of the edge server to maintain virtual object spatial-temporal consistency in neighboring devices by synchronizing a local graph. We…
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Taxonomy
TopicsAugmented Reality Applications
