• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Palette-based Color Attribute Compression for Point Cloud Data

Vol. 13, No. 6, June 29, 2019
10.3837/tiis.2019.06.019, Download Paper (Free):

Abstract

Point cloud is widely used in 3D applications due to the recent advancement of 3D data acquisition technology. Polygonal mesh-based compression has been dominant since it can replace many points sharing a surface with a set of vertices with mesh structure. Recent point cloud-based applications demand more point-based interactivity, which makes point cloud compression (PCC) becomes more attractive than 3D mesh compression. Interestingly, an exploration activity has been started to explore the feasibility of PCC standard in MPEG. In this paper, a new color attribute compression method is presented for point cloud data. The proposed method utilizes the spatial redundancy among color attribute data to construct a color palette. The color palette is constructed by using K-means clustering method and each color data in point cloud is represented by the index of its similar color in palette. To further improve the compression efficiency, the spatial redundancy between the indices of neighboring colors is also removed by marking them using a flag bit. Experimental results show that the proposed method achieves a better improvement of RD performance compared with that of the MPEG PCC reference software.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
L. Cui and E. S. Jang, "Palette-based Color Attribute Compression for Point Cloud Data," KSII Transactions on Internet and Information Systems, vol. 13, no. 6, pp. 3108-3120, 2019. DOI: 10.3837/tiis.2019.06.019.

[ACM Style]
Li Cui and Euee S. Jang. 2019. Palette-based Color Attribute Compression for Point Cloud Data. KSII Transactions on Internet and Information Systems, 13, 6, (2019), 3108-3120. DOI: 10.3837/tiis.2019.06.019.