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Holes filling of scattered point cloud based on simplification

  • 1198: Advances in Multimedia Interaction and Visualization
  • Published:
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Abstract

To address the problem of feature points missing and surface holes after 3D reconstruction. A method of filling holes after extracting feature points of point cloud data is proposed. In this paper, the method of extracting feature points by multi-discriminant parameters is used to simplify the point cloud. The original shape features are retained while the data are simplified. Then, the initial triangulation of the point cloud is carried out. The resulting triangular mesh is least squared to get a relatively normal mesh, and finally the curvature of the surface is adjusted and optimized. The experimental results show that the simplification rate corresponding to improving the efficiency and retaining the original features is different for the point cloud data of different magnitude. The simplification rate of tens of thousands point cloud data is 70-80%, and that of hundreds of thousands of point cloud data is 40%. It also shows that the combination of feature point extraction and hole repair not only improves the efficiency of the repair process, but also retains the original features of the data.

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Acknowledgements

This work was supported by National Natural Science Foundation oc China (Grant No.51705304), Natrual Science Foundation of Shanghai(Grant No.20ZR1421300).

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  1. College of Automation Engineering, Shanghai University of Electric Power, Shanghai, 200090, China

    Hui Chen & Wen Cui

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  1. Hui Chen
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  2. Wen Cui
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Correspondence to Hui Chen.

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Chen, H., Cui, W. Holes filling of scattered point cloud based on simplification. Multimed Tools Appl 81, 14641–14661 (2022). https://doi.org/10.1007/s11042-021-11019-3

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