Method for building grid surface by organism point clouds

Abstract

The invention discloses a method for building a grid by organism point clouds. By the aid of the method, reconstruction quality is improved, reconstruction is accelerated, and the reconstruction process is more efficient. The method includes the steps: performing Delaunay triangulation for point cloud data to obtain triangles with arbitrary adjacent boundaries; dividing a region to obtain different growing regions and determining the growing direction of each growing region; selecting a triangle at a center in each growing region as a seed triangle, placing the seed triangles into a set T1 and placing the boundaries of the seed triangles into a set E; placing triangles with adjacent sides of the seed triangles into a set T2 and replacing elements in the set E with boundaries of elements in the set T2; placing triangles with adjacent sides of the elements in the set T2 into the set T3; comparing an included angle between a mass center connecting line of each element in the T1 and each element in the T3, and the growing direction; adding triangles with the smallest included angle and triangles with the largest included angle into a reconstruction grid surface; and replacing the elements in the T1 into the elements in the T2 and repeating the steps until reconstruction of the whole grid surface is finished.

Description

technical field [0001] The invention belongs to the field of digital geometric model processing, and is specifically applied to constructing a living body surface from point cloud data into a grid surface. Background technique [0002] Traditional 3D object surface reconstruction includes the following methods: [0003] 1. Poisson surface reconstruction, based on the Poisson equation, is an implicit function method that combines global fitting and local fitting. The Poisson reconstruction method combines the advantages of global and local fitting methods, and does not involve heuristic decisions when forming adjacent regions, selecting patch types, and adjusting weights. Moreover, the basis function and the surrounding space are not data-point-correlated but locally supported, and have a hierarchical structure, thus forming a sparse well-conditioned system. [0004] The specific reconstruction steps are: [0005] 1. Define the octree; [0006] Define an adaptive octree t...

AI Technical Summary

Problems solved by technology

[0016] Although fine curved surfaces can be constructed using this method, there are obvious distortions in the reconstruction of objects with sharp edges and corners.

[0017] The surface reconstruction of point cloud is an ill-conditioned solution problem. Due to the huge amount of point cloud data and the complex surface conditions of rigid bodies, it is a very challenging task.

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