KEYWORDS: Clouds, 3D modeling, Reconstruction algorithms, 3D metrology, Data modeling, Reverse modeling, RGB color model, 3D acquisition, Surface plasmons, Optical filters
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.
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