Three-dimensional point cloud reconstruction method based on improved shield poisson algorithm

Abstract

The invention discloses a three-dimensional point cloud reconstruction method based on improved shield poisson algorithm. The method comprises the following steps: obtaining a three-dimensional point cloud data of a model; introducing shielding factor, and preprocessing the constraint of the poisson algorithm by the constraint of the introduction point and the gradient; using the octree segmentation to simplify the denoising of the point cloud, compressing the storage, establishing the inter-cloud topology, and realizing the fast establishment and efficient searching of the octagonal tree neighbor nodes; normalizing each point cloud vector to reduce the ambiguity of normal direction; calculating the vector field; solving poisson equation to get instruction function; on point cloud equivalent surface extraction, getting three-dimensional reconstruction model. The method of the three-dimensional point cloud reconstruction method based on improved shield poisson algorithm has the advantages of improving the normal vector precision, removing the pseudo-closed surface well, and being well filled with the hole, and the detail of the object is rich. The method can be widely used in the fields of reverse engineering, cultural restoration, and medical image.

Description

technical field [0001] The invention relates to the field of three-dimensional reconstruction, in particular to a three-dimensional point cloud reconstruction method based on an improved masked Poisson algorithm. Background technique [0002] 3D point cloud reconstruction of object surfaces is a hot research issue in computer graphics. Because equipment and acquisition methods will produce point clouds that contain a variety of defects that can cause surface reconstruction methods, it poses a major challenge to 3D reconstruction. [0003] Normal information is an important property of surface reconstruction, and its accuracy determines the accuracy of reconstruction algorithms. Due to the lack of topological connections between point cloud data, there are certain difficulties in normal vector estimation and reorientation. For the estimation of normal direction, there are mainly three types: methods based on Delaunay / Voronoi, methods based on robust statistics and methods ba...

AI Technical Summary

Problems solved by technology

[0002] 3D point cloud reconstruction of object surfaces is a hot research issue in computer graphics. Because equipment and acquisition methods will produce point clouds that contain a variety of defects that can cause surface reconstruction methods, it poses a major challenge to 3D reconstruction.

However, the Poisson surface reconstruction algorithm process does not introduce information related to the shape of the model, so it is easy to automatically reconstruct a non-closed point cloud to generate a large number of irregular and inappropriate pseudo-surfaces, which affects the surface reconstruction effect

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