loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Albert Christensen ; Daniel Lehotský ; Mathias Poulsen and Thomas Moeslund

Affiliation: Visual Analysis and Perception Lab, Aalborg University, Rendsburggade 14, DK-9000, Aalborg, Denmark

Keyword(s): Point Cloud Compression, 3D Compression, V-PCC, G-PCC, Draco, Performance Comparison Pipeline.

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.145.161.194

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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; ISSN 2184-4321, SciTePress, pages 387-393. DOI: 10.5220/0010820200003124

@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},
issn={2184-4321},
}

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
IS - 2184-4321
AU - Christensen, A.
AU - Lehotský, D.
AU - Poulsen, M.
AU - Moeslund, T.
PY - 2022
SP - 387
EP - 393
DO - 10.5220/0010820200003124
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic