Sparse representation three-dimensional point cloud compression method adopting geometric guidance

A technology of 3D point cloud and sparse representation, applied in the field of video coding, to achieve the effect of efficient coding, eliminating color redundancy and reducing the amount of data

Active Publication Date: 2019-09-24
HUAQIAO UNIVERSITY
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  • Application Information

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Problems solved by technology

With the progress of research work, sparse representation can be used to efficiently compress high-dimensional data, but how to establish a redundant dictionary and sparsely represent the color information of the point cloud on the redundant dictionary is still a difficult problem to be solved

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  • Sparse representation three-dimensional point cloud compression method adopting geometric guidance
  • Sparse representation three-dimensional point cloud compression method adopting geometric guidance
  • Sparse representation three-dimensional point cloud compression method adopting geometric guidance

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Embodiment Construction

[0026] The present invention will be further described below through specific embodiments.

[0027] see figure 1 , a geometry-guided sparse representation 3D point cloud compression method, performs octree segmentation on the input 3D point cloud, then assumes that the voxels in each block are occupied, and uses graph transformation to obtain the original redundant dictionary, And the downsampled redundant dictionary is obtained through the geometric information in each block. Then the color information in each block is sparsely represented on the downsampled redundant dictionary to obtain sparse coefficients. The mean value of each block is predictively coded and quantized by using the octree-based block mean value prediction method of the present invention. The quantized sparse coefficients use the Run-Level encoding method to encode the non-zero coefficients. Finally, all encoding parameters are entropy-encoded using an algorithmic encoder. The specific implementation s...

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Abstract

The invention discloses a sparse representation three-dimensional point cloud compression method adopting geometric guidance, and belongs to the field of video coding. The method comprises the steps of partitioning an input three-dimensional point cloud through an octree; obtaining an original redundant dictionary by adopting a graphic transformation method; down-sampling the original redundant dictionary by using the geometrical information of the point cloud in the block; carrying out mean value removal on each unit block, and then carrying out sparse representation on the color information subjected to mean value removal on a down-sampling dictionary; performing predictive coding on the mean value of each coding unit block by utilizing a block mean value prediction algorithm based on the octree; encoding the quantized sparse coefficient by adopting a Run-Level method; and finally, carrying out entropy coding on all coded parameters by using an arithmetic coder. According to the method, by utilizing the sparse representation, the huge three-dimensional point cloud data can be efficiently compressed, and the transmission and storage efficiency of the three-dimensional point cloud is greatly improved.

Description

technical field [0001] The invention relates to the field of video coding, in particular to a geometrically guided sparse representation three-dimensional point cloud compression method. Background technique [0002] With the rapid development of 3D acquisition and multimedia communication technology, 3D point cloud as a new transmission medium is widely used in many fields such as remote communication, augmented reality, and immersive communication. The 3D point cloud is composed of a large number of point sets with specific 3D position information, where each point has one or more features (such as: color, normal, etc.). As a new type of spatial data, 3D point cloud can more effectively represent 3D objects or scenes with more complex topology. But its huge amount of data brings great challenges to its storage and transmission. Therefore, how to construct an efficient and stable 3D point cloud compression method is particularly important. [0003] Different from traditi...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N19/96H04N19/91H04N19/124H04N19/103H04N19/597H04N19/176H04N19/64
CPCH04N19/96H04N19/91H04N19/124H04N19/103H04N19/597H04N19/176H04N19/64
Inventor 曾焕强谷帅侯军辉陈婧朱建清张联昌
Owner HUAQIAO UNIVERSITY
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