System and method for converting disordered point cloud to triangular net based on adaptive flatness

Abstract

A system and method for converting unordered point clouds into triangular meshes based on adaptive flatness, through the incremental reconstruction algorithm of unordered point cloud grids based on adaptive flatness, the point cloud is directly triangulated in space , starting from the initial center point to construct a local mesh ring according to the flat characteristics of the surface and the Delaunay triangulation rule, and according to the generation sequence, the point on the boundary of the mesh ring is used as the center point to repeatedly construct the local ring, and the loop is linearly propagated to The entire point set finally obtains the corresponding topological structure to improve the conversion speed and reduce the conversion time. At the same time, it can effectively avoid the deformation and jaggedness caused by the conversion process, and achieve better processing of closed surfaces or approximately closed surfaces.

Description

technical field [0001] The invention relates to a system and method for converting disordered point clouds into triangular meshes based on adaptive flatness. Background technique [0002] The surface reconstruction of massive scattered point data is widely used in many fields such as mechanical product measurement and modeling, geographic information system and so on. Among them, the reconstruction of triangular meshes has been a hot research topic at home and abroad. Boissonnate first used 3D Delaunay-based tetrahedronization for interpolation grid construction, and Nina Amenta proposed a Crust-based tetrahedronization engraving algorithm, which theoretically ensures that the reconstructed mesh model is topologically consistent with the underlying geometric model. However, the grids constructed by such algorithms are all based on Delaunay tetrahedronization, and the time consumption is 0(n2), which is difficult to apply to large-scale data. Chen directly determines the mi...

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Problems solved by technology

This method first needs to project the three-dimensional data points to the two-dimensional plane, which leads to difficulties in processing closed surfaces or approximately closed surfaces. It is also difficult to find a suitable projection plane for more complex surfaces. Gopi and Crossno proposed a method based on local two-dimensional Dimensional Delaunay triangular mesh incremental construction algorithm, although these have achieved linear reconstruction of the mesh, but it is difficult to guarantee the mesh quality

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