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3D point cloud inpainting method based on local smoothness and non-local similarity

A technology of 3D point cloud and repair method, which is applied in the field of point cloud repair, and can solve the problems of easy artifacts and distortions on the boundary

Active Publication Date: 2020-10-16
PEKING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

This kind of method completely relies on the local information around the hole to repair. Since the reference information is relatively simple, the repair result is more flat than the actual content, which is easy to be distorted, and when the geometric structure is complex, the repaired boundary is prone to artifacts

Method used

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  • 3D point cloud inpainting method based on local smoothness and non-local similarity
  • 3D point cloud inpainting method based on local smoothness and non-local similarity
  • 3D point cloud inpainting method based on local smoothness and non-local similarity

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Embodiment Construction

[0041]In order to make the above-mentioned features and advantages of the present invention more comprehensible, the following specific embodiments are described in detail in conjunction with the accompanying drawings.

[0042] Aiming at the method of the present invention, firstly introduce the basic concepts in the spectral graph theory, and then propose the eigenvector frequency interpretation based on the graph node domain, the spectral graph theory will be the core of the method in the invention. The spectrum theory includes the following contents:

[0043] (1) Graph and graph Laplacian operator:

[0044] Define an undirected graph, G={V,E,W}. V is the set of vertices on the graph, |V|=N; E is the set of edges; W is the weighted adjacency matrix. where W is a N×N real symmetric matrix, w i,j is the weight of the edge connecting vertex i to vertex j, and usually uses a non-negative value as the weight.

[0045] The graph Laplacian is usually defined as L=D-W, where D i...

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Abstract

The invention provides a three-dimensional point cloud restoration method based on local smoothness and non-local similarity, and relates to the field of graph signal processing, and the method comprises the main steps: voxelization of point cloud, detection of point cloud holes, search of similar areas, matching of relative positions, and restoration of missing areas. According to the method, thecomplex geometric structure can be well repaired, the loss of the geometric structure is reduced, artifacts are not generated, and the repair fidelity is high.

Description

technical field [0001] The invention relates to the field of point cloud restoration, and its theoretical basis relates to the field of image signal processing, in particular to a three-dimensional point cloud restoration method based on local smoothness and non-local similarity. Background technique [0002] Point cloud data collected by 3D scanners and depth sensing will inevitably produce data errors: for some areas that cannot be scanned, they will be presented in the form of holes with missing data in the scanning results. Reasons for missing data include incomplete scanning angles, limitations of laser scanners, and complex geometric structures of objects. [0003] In terms of hole detection, there are currently two mainstream algorithms: grid-based methods and point-based methods. [0004] The grid-based method is mainly to construct a grid on the point cloud. Emelyanov et al., Orriols et al., and Floater et al. extract hole boundaries through some greedy strategies,...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T17/20
Inventor 胡玮傅泽卿郭宗明
Owner PEKING UNIV
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