@inproceedings{e3857614305d46f0a90f2354cd08f480,
title = "Presenting a Novel Pipeline for Performance Comparison of V-PCC and G-PCC Point Cloud Compression Methods on Datasets with Varying Properties",
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{\textquoteright}s G-PCC octree RAHT and MPEG{\textquoteright}s V-PCC compression codecs.",
author = "Christensen, {Albert Daugbjerg} and Daniel Lehotsk{\'y} and Poulsen, {Mathias {\O}stergaard} and Moeslund, {Thomas B.}",
year = "2022",
month = feb,
doi = "10.5220/0010820200003124",
language = "English",
series = "International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications",
publisher = "SciTePress",
pages = "387--393",
booktitle = "Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications",
note = "17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications ; Conference date: 06-02-2022 Through 08-02-2022",
}