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Main Authors: Gautier, Guillaume, Mercat, Alexandre, Fréneau, Louis, Pitkänen, Mikko, Vanne, Jarno
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2504.05888
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author Gautier, Guillaume
Mercat, Alexandre
Fréneau, Louis
Pitkänen, Mikko
Vanne, Jarno
author_facet Gautier, Guillaume
Mercat, Alexandre
Fréneau, Louis
Pitkänen, Mikko
Vanne, Jarno
contents Point cloud compression has become a crucial factor in immersive visual media processing and streaming. This paper presents a new open dataset called UVG-VPC for the development, evaluation, and validation of MPEG Visual Volumetric Video-based Coding (V3C) technology. The dataset is distributed under its own non-commercial license. It consists of 12 point cloud test video sequences of diverse characteristics with respect to the motion, RGB texture, 3D geometry, and surface occlusion of the points. Each sequence is 10 seconds long and comprises 250 frames captured at 25 frames per second. The sequences are voxelized with a geometry precision of 9 to 12 bits, and the voxel color attributes are represented as 8-bit RGB values. The dataset also includes associated normals that make it more suitable for evaluating point cloud compression solutions. The main objective of releasing the UVG-VPC dataset is to foster the development of V3C technologies and thereby shape the future in this field.
format Preprint
id arxiv_https___arxiv_org_abs_2504_05888
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle UVG-VPC: Voxelized Point Cloud Dataset for Visual Volumetric Video-based Coding
Gautier, Guillaume
Mercat, Alexandre
Fréneau, Louis
Pitkänen, Mikko
Vanne, Jarno
Multimedia
Computer Vision and Pattern Recognition
Point cloud compression has become a crucial factor in immersive visual media processing and streaming. This paper presents a new open dataset called UVG-VPC for the development, evaluation, and validation of MPEG Visual Volumetric Video-based Coding (V3C) technology. The dataset is distributed under its own non-commercial license. It consists of 12 point cloud test video sequences of diverse characteristics with respect to the motion, RGB texture, 3D geometry, and surface occlusion of the points. Each sequence is 10 seconds long and comprises 250 frames captured at 25 frames per second. The sequences are voxelized with a geometry precision of 9 to 12 bits, and the voxel color attributes are represented as 8-bit RGB values. The dataset also includes associated normals that make it more suitable for evaluating point cloud compression solutions. The main objective of releasing the UVG-VPC dataset is to foster the development of V3C technologies and thereby shape the future in this field.
title UVG-VPC: Voxelized Point Cloud Dataset for Visual Volumetric Video-based Coding
topic Multimedia
Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2504.05888