Multi-view Data Capture using Edge-synchronised Mobiles

Matteo Bortolon, Paul Chippendale, Stefano Messelodi, Fabio Poiesi

2020

Abstract

Multi-view data capture permits free-viewpoint video (FVV) content creation. To this end, several users must capture video streams, calibrated in both time and pose, framing the same object/scene, from different viewpoints. New-generation network architectures (e.g. 5G) promise lower latency and larger bandwidth connections supported by powerful edge computing, properties that seem ideal for reliable FVV capture. We have explored this possibility, aiming to remove the need for bespoke synchronisation hardware when capturing a scene from multiple viewpoints, making it possible through off-the-shelf mobiles. We propose a novel and scalable data capture architecture that exploits edge resources to synchronise and harvest frame captures. We have designed an edge computing unit that supervises the relaying of timing triggers to and from multiple mobiles, in addition to synchronising frame harvesting. We empirically show the benefits of our edge computing unit by analysing latencies and show the quality of 3D reconstruction outputs against an alternative and popular centralised solution based on Unity3D.

Paper Citation

in Harvard Style

Bortolon M., Chippendale P., Messelodi S. and Poiesi F. (2020). Multi-view Data Capture using Edge-synchronised Mobiles. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP; ISBN 978-989-758-402-2, SciTePress, pages 730-740. DOI: 10.5220/0008971807300740

in Bibtex Style

@conference{visapp20,
author={Matteo Bortolon and Paul Chippendale and Stefano Messelodi and Fabio Poiesi},
title={Multi-view Data Capture using Edge-synchronised Mobiles},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP},
year={2020},
pages={730-740},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008971807300740},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP
TI - Multi-view Data Capture using Edge-synchronised Mobiles
SN - 978-989-758-402-2
AU - Bortolon M.
AU - Chippendale P.
AU - Messelodi S.
AU - Poiesi F.
PY - 2020
SP - 730
EP - 740
DO - 10.5220/0008971807300740
PB - SciTePress