Synthesising Light Field Volumetric Visualizations in Real-time using a Compressed Volume Representation

Seán Bruton, David Ganter, Michael Manzke

Abstract

Light field display technology will permit visualization applications to be developed with enhanced perceptual qualities that may aid data inspection pipelines. For interactive applications, this will necessitate an increase in the total pixels to be rendered at real-time rates. For visualization of volumetric data, where ray-tracing techniques dominate, this poses a significant computational challenge. To tackle this problem, we propose a deep-learning approach to synthesise viewpoint images in the light field. With the observation that image content may change only slightly between light field viewpoints, we synthesise new viewpoint images from a rendered subset of viewpoints using a neural network architecture. The novelty of this work lies in the method of permitting the network access to a compressed volume representation to generate more accurate images than achievable with rendered viewpoint images alone. By using this representation, rather than a volumetric representation, memory and computation intensive 3D convolution operations are avoided. We demonstrate the effectiveness of our technique against newly created datasets for this viewpoint synthesis problem. With this technique, it is possible to synthesise the remaining viewpoint images in a light field at real-time rates.

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Paper Citation


in Harvard Style

Bruton S., Ganter D. and Manzke M. (2019). Synthesising Light Field Volumetric Visualizations in Real-time using a Compressed Volume Representation.In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP, ISBN 978-989-758-354-4, pages 96-105. DOI: 10.5220/0007407200960105


in Bibtex Style

@conference{ivapp19,
author={Seán Bruton and David Ganter and Michael Manzke},
title={Synthesising Light Field Volumetric Visualizations in Real-time using a Compressed Volume Representation},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,},
year={2019},
pages={96-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007407200960105},
isbn={978-989-758-354-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,
TI - Synthesising Light Field Volumetric Visualizations in Real-time using a Compressed Volume Representation
SN - 978-989-758-354-4
AU - Bruton S.
AU - Ganter D.
AU - Manzke M.
PY - 2019
SP - 96
EP - 105
DO - 10.5220/0007407200960105