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Probability model-adaptive coding of point clouds with octree decomposition

Published: 12 December 2011 Publication History

Abstract

An important observation is that when compressing point clouds using Octree (OT) decomposition based compression algorithms [Peng and Kuo 2005; Huang et al. 2008], the octree nodes with only one non-empty child (single-point nodes), occur in an increasing frequency as the cell subdivision goes deeper. The commonly employed entropy codec uses a probability model which keeps updating during the coding process. However, as illustrated in Fig.1 (b), the symbol distribution keeps varying and thus the probability model trained online is seldom perfectly matched with the real statistical distribution. Thus, there is still much room left to further save the bitrates when using these codecs.

References

[1]
Huang, Y., Peng, J., Kuo, C. C. J., and Gopi, M. 2008. A generic scheme for progressive point cloud coding. IEEE Transactions on Visualization and Computer Graphics 14, 440--453.
[2]
Peng, J., and Kuo, C.-C. J. 2005. Geometry-guided progressive lossless 3d mesh coding with octree (ot) decomposition. ACM Trans. Graph. 24, 3, 609--616.

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  • (2017)Lossless point cloud geometry compression via binary tree partition and intra prediction2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP)10.1109/MMSP.2017.8122226(1-6)Online publication date: Oct-2017

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            cover image ACM Conferences
            SA '11: SIGGRAPH Asia 2011 Posters
            December 2011
            61 pages
            ISBN:9781450311373
            DOI:10.1145/2073304
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            Published: 12 December 2011

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            SA '11: SIGGRAPH Asia 2011
            December 12 - 15, 2011
            Hong Kong, China

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            • (2017)Lossless point cloud geometry compression via binary tree partition and intra prediction2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP)10.1109/MMSP.2017.8122226(1-6)Online publication date: Oct-2017

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