Projected area measurement of complex 3D objects based on point cloud data

Lujing Qian; Yubang Yang; Shuyu Sun; Tengchao Huang

doi:10.1117/12.2606375

24 November 2021 Projected area measurement of complex 3D objects based on point cloud data

Lujing Qian, Yubang Yang, Shuyu Sun, Tengchao Huang

Proceedings Volume 12065, AOPC 2021: Optical Sensing and Imaging Technology; 120652B (2021) https://doi.org/10.1117/12.2606375
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China

Abstract

In this paper, a novel method for measuring the projected area of complex 3D objects based on lidar point cloud data is present. To solve the problem of partial data missing in the process of collection, a method of combining Moving Least Squares (MLS) and greedy projection triangulation algorithm for 3D surface reconstruction is proposed. Combined with the MLS method, the problem of greedy projection triangulation method that it requires the point cloud density to change uniformly is made up. The surface data obtained by this method is smoother and the number of holes is reduced, so that the final projected area calculated is much more accurate. The point cloud display platform is written in C++ under Win10 environment. We select PCL to render point clouds and grids and use VTK framework to implement visual interface, which can display the algorithm results of this article.

Citation Download Citation

Lujing Qian, Yubang Yang, Shuyu Sun, and Tengchao Huang "Projected area measurement of complex 3D objects based on point cloud data", Proc. SPIE 12065, AOPC 2021: Optical Sensing and Imaging Technology, 120652B (24 November 2021); https://doi.org/10.1117/12.2606375

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