Impact of Geometry and Attribute Distortion in Subjective Quality of Point Clouds for G-PCC

Zhang Chen, Shuai Wan, Fuzheng Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

To better understand the effect of geometry and attribute distortion on the subjective quality of point clouds, we built a database with subjective quality scores for compressed point clouds. We analyzed the impact of geometry and attribute distortion to subjective quality. Our database, named the NWPU Point Cloud Quality Database (NWPU-PCQD), contains 817 point clouds with various geometry and attribute quantification distortions, which were subjectively evaluated using head-mounted displays (HMDs). Through correlation and significance analysis of the subjective quality scores, we observe that geometry and attribute quantization do not equally contribute to the overall subjective quality, where the effect of geometry quantization dominates. Moreover, there is an interaction between the geometry and attribute distortion. Our subjective database and findings are useful for point cloud processing, transmission, and compression.

Original languageEnglish
Title of host publication2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350359855
DOIs
StatePublished - 2023
Event2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023 - Jeju, Korea, Republic of
Duration: 4 Dec 20237 Dec 2023

Publication series

Name2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023

Conference

Conference2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023
Country/TerritoryKorea, Republic of
CityJeju
Period4/12/237/12/23

Keywords

  • Point cloud compression
  • Point clouds
  • Subjective quality

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