A Method for Computing 3D Point Cloud Model Skeleton

Abstract

The invention discloses a method used for calculating a three-dimensional point cloud model bone. The method provided by the invention comprises the steps that a gradual breakdown policy is used to carry out even voxelization on a three-dimensional point cloud model; a fast marching algorithm is used to calculate the distance field of voxel points in the model; the distance field is used to calculate the initial bone of the model; and the initial bone and an L1 mid-value bone extraction algorithm are fused to generate an L1 mid-value bone extraction algorithm based on the distance field, and the model bone is quickly and accurately calculated. Compared with the existing three-dimensional point cloud model bone extraction method, the method provided by the invention has the advantages that the point cloud model with a lot of noise points, singular points and large-area point cloud missing are processed; false bone connection is prevented; and the method does not need too many parameters.

Description

Technical field [0001] The invention belongs to the technical field of graphics processing, and in particular relates to a method for extracting bones from a three-dimensional point cloud model. Background technique [0002] With the popularity of 3D scanning equipment, the number of 3D point cloud models is increasing. However, the 3D point cloud obtained by ordinary 3D scanning equipment, due to the accuracy of the hardware itself, the shooting angle, the illumination, the mutual occlusion of the 3D objects, and the improper use of the device by the user, the generated point cloud model contains a large number of noise points, singular points and large areas The point cloud is missing. Model bones have many applications. For example, in medicine, bones can be used for endoscopy. In addition, in computer graphics, bones can be used to control the movement of character mesh models, generate skeletal animations, and can also be used to drive point cloud models. Perform registrat...

AI Technical Summary

Problems solved by technology

[0003] However, the acquisition of 3D model skeletons is still a big problem, especially for models obtained by direct scanning, with a lot of noise and large areas of missing point clouds

First of all, because the point cloud model has no topological connection information, it is difficult to extract bones through the model topological relationship

Secondly, the quality of the point cloud model is poor, often there is a large area of ​​point cloud missing, a large number of noise points and singular points, which increases the difficulty of bone extraction

Finally, bone extraction is a morbid problem. In order to calculate better bone results, the existing bone extraction methods need to adjust a large number of parameters, which reduces the practicability of the algorithm.

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