Hybrid color attribute compression for point cloud data

Li Cui, Hai Yan Xu, Euee S. Jang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

This paper proposes a color attribute compression method for MPEG Point Cloud Compression (PCC) by exploiting the spatial redundancy among the adjacent points. With the increased interest in representing real-world surface as 3D point clouds, compressing the attributes (i.e., colors and normal directions) of point cloud has attracted great attention in MPEG. The proposed method is based on grouping the adjacent points in blocks. And two encoding modes are supported for each block, which include the run-length encoding mode and palette mode. The final encoding mode for each block is determined through comparing two distortion values based on two encoding modes. Experimental results show that the proposed approach achieves about 28 percent compression ratio than that of MPEG PCC.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Multimedia and Expo, ICME 2017
PublisherIEEE Computer Society
Pages1273-1278
Number of pages6
ISBN (Electronic)9781509060672
DOIs
Publication statusPublished - 2017 Aug 28
Event2017 IEEE International Conference on Multimedia and Expo, ICME 2017 - Hong Kong, Hong Kong
Duration: 2017 Jul 102017 Jul 14

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Other

Other2017 IEEE International Conference on Multimedia and Expo, ICME 2017
CountryHong Kong
CityHong Kong
Period17/07/1017/07/14

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Keywords

  • Color attribute
  • Color palette
  • Point cloud compression
  • Rate distortion cost
  • Run-length encoding

Cite this

Cui, L., Xu, H. Y., & Jang, E. S. (2017). Hybrid color attribute compression for point cloud data. In 2017 IEEE International Conference on Multimedia and Expo, ICME 2017 (pp. 1273-1278). [8019426] (Proceedings - IEEE International Conference on Multimedia and Expo). IEEE Computer Society. https://doi.org/10.1109/ICME.2017.8019426