A Generic Scheme for Progressive Point Cloud Coding

In this paper, we propose a generic point cloud encoder that provides a unified framework for compressing different attributes of point samples corresponding to 3D objects with an arbitrary topology. In the proposed scheme, the coding process is led by an iterative octree cell subdivision of the obj...

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Bibliographic Details
Published in:IEEE transactions on visualization and computer graphics 2008-03, Vol.14 (2), p.440-453
Main Authors: Yan Huang, Jingliang Peng, Kuo, C.-C.J., Gopi, M.
Format: Article
Language:English
Subjects:
Animation
Clouds
Coders
Coding
Computer science
Data compaction and compression
Decoding
Encoders
Encoding
Geometry
Indexing methods
Object hierarchies
Quantization
Rate-distortion
Samples
Solid modeling
Statistical methods
Subdivisions
Three dimensional
Topology
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Summary:In this paper, we propose a generic point cloud encoder that provides a unified framework for compressing different attributes of point samples corresponding to 3D objects with an arbitrary topology. In the proposed scheme, the coding process is led by an iterative octree cell subdivision of the object space. At each level of subdivision, the positions of point samples are approximated by the geometry centers of all tree-front cells, whereas normals and colors are approximated by their statistical average within each of the tree-front cells. With this framework, we employ attribute-dependent encoding techniques to exploit the different characteristics of various attributes. All of these have led to a significant improvement in the rate-distortion (R-D) performance and a computational advantage over the state of the art. Furthermore, given sufficient levels of octree expansion, normal space partitioning, and resolution of color quantization, the proposed point cloud encoder can be potentially used for lossless coding of 3D point clouds.
ISSN:1077-2626
1941-0506
DOI:10.1109/TVCG.2007.70441