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

A triangular mesh and flatness technology, applied in the direction of filling the plane with attributes, can solve problems such as difficulty in ensuring the quality of the mesh, difficulty in finding the projection plane, and difficulty in processing, so as to avoid deformation and jaggedness, reduce conversion time, and improve The effect of conversion speed

Inactive Publication Date: 2007-11-07
TONGJI UNIV
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AI Technical Summary

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

Method used

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

Examples

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Example

[0049] Example 1:

[0050] The data of each point of the disordered point cloud is shown in Figure 5a. After the conversion of the present invention, the corresponding triangular grid is obtained. As shown in Figure 5b, the time required for a total of 3189 points is 6 seconds. The final drawing effect is shown in Figure Shown in 5c.

Example

[0051] Example 2:

[0052] The data of each point of the disordered point cloud is shown in Figure 6a, Figure 6b is the partial reconstruction result of the triangular mesh (in order to show the reconstructed triangular patch more clearly, the partial enlarged mesh effect is given here), and Figure 6c is the final drawing result. There are a total of 51920 point cloud data, and 42876 triangle patches are generated, which takes 117 seconds. It can also be illustrated by this example that the present invention can better handle the inner and outer boundaries.

[0053] In summary, the present invention avoids the high-complexity calculation caused by the tetrahedral division. In general, the time complexity of the tetrahedral triangulation algorithm for a set of scattered points in space is 0 (n2). However, the present invention is used to preprocess the point cloud, and the method of spatial direct triangulation is adopted, thereby ensuring that when the number of points is large, t...

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Abstract

This invention relates to a system and a method for converting non-sequence spot-clouds into triangle griddings based on adaptive flatness, which carries out triangle analysis to spot-clouds in space directly by a non-sequence spot-cloud increment rebuilding algorithm based on adaptive flatness to structure a partial gridding ring from the initial central point based on the partial flat character of a curvature face and a Delaunary analysis rule of triangles and takes points on said gridding ring as the central point according to the generation sequence to structure the partial ring repeatedly to circulate in linearity and spread it to the entire spot set and get a topological structure finally so as to increase conversion velocity and reduce conversion time.

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...

Claims

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Application Information

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IPC IPC(8): G06T11/40
Inventor 郝泳涛
Owner TONGJI UNIV
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