Presenting a Novel Pipeline for Performance Comparison of V-PCC and G-PCC Point Cloud Compression Methods on Datasets with Varying Properties

Albert Christensen, Daniel Lehotský, Mathias Poulsen, Thomas Moeslund

2022

Abstract

The increasing availability of 3D sensors enables an ever increasing amount of applications to utilize 3D captured content in the form of point clouds. Several promising methods for compressing point clouds have been proposed but lacks a unified method for evaluating their performance on a wide array of point cloud datasets with different properties. We propose a pipeline for evaluating the performance of point cloud compression methods on both static and dynamic point clouds. The proposed evaluation pipeline is used to evaluate the performance of MPEG’s G-PCC octree RAHT and MPEG’s V-PCC compression codecs.

Paper Citation

in Harvard Style

Christensen A., Lehotský D., Poulsen M. and Moeslund T. (2022). Presenting a Novel Pipeline for Performance Comparison of V-PCC and G-PCC Point Cloud Compression Methods on Datasets with Varying Properties. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5, SciTePress, pages 387-393. DOI: 10.5220/0010820200003124

in Bibtex Style

@conference{visapp22,
author={Albert Christensen and Daniel Lehotský and Mathias Poulsen and Thomas Moeslund},
title={Presenting a Novel Pipeline for Performance Comparison of V-PCC and G-PCC Point Cloud Compression Methods on Datasets with Varying Properties},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={387-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010820200003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Presenting a Novel Pipeline for Performance Comparison of V-PCC and G-PCC Point Cloud Compression Methods on Datasets with Varying Properties
SN - 978-989-758-555-5
AU - Christensen A.
AU - Lehotský D.
AU - Poulsen M.
AU - Moeslund T.
PY - 2022
SP - 387
EP - 393
DO - 10.5220/0010820200003124
PB - SciTePress