TY - GEN
T1 - UVG-VPC
T2 - International Conference on Quality of Multimedia Experience
AU - Gautier, Guillaume
AU - Mercat, Alexandre
AU - Fréneau, Louis
AU - Pitkänen, Mikko
AU - Vanne, Jarno
N1 - Funding Information:
This work was supported in part by the XR Simulation and Presence at the Cloud Edge (XR-SPACE) project led by Nokia and funded by Business Finland, and the Academy of Finland (decision no. 349216). This work was carried out with the support of Centre for Immersive Visual Technologies (CIVIT) research infrastructure, Tampere University, Finland. In addition, the authors wish to acknowledge CSC IT Center for Science, Finland, for computational and storage resources.
Funding Information:
This work was supported in part by the XR Simulation and Presence at the Cloud Edge (XR-SPACE) project led by Nokia and funded by Business Finland, and the Academy of Finland (decision no. 349216).
Funding Information:
ACKNOWLEDGMENT This work was carried out with the support of Centre for Immersive Visual Technologies (CIVIT) research infrastructure, Tampere University, Finland. In addition, the authors wish to acknowledge CSC – IT Center for Science, Finland, for computational and storage resources.
Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Extended Reality (XR)
KW - Open dataset
KW - point cloud
KW - Video-based Point Cloud Compression (V-PCC)
KW - Visual Volumetric Video-based Coding (V3C)
U2 - 10.1109/QoMEX58391.2023.10178589
DO - 10.1109/QoMEX58391.2023.10178589
M3 - Conference contribution
AN - SCOPUS:85167353197
T3 - International Conference on Quality of Multimedia Experience
SP - 244
EP - 247
BT - 2023 15th International Conference on Quality of Multimedia Experience, QoMEX 2023
PB - IEEE
Y2 - 20 June 2023 through 22 June 2023
ER -