Triangular mesh model optimization method

Abstract

The invention discloses a triangular mesh model optimization method, which can be used for effectively optimizing a triangular mesh model to obtain a sampling mesh similar to an original mesh. The method comprises the following steps of (1) performing self-adapting sampling based on vertex uniform division; (2) calculating the Hausdorff distance H1 from each surface of the original mesh to the re-sampled mesh surface, and the Hausdorff distance H2 from each surface of the re-sampled mesh to the original mesh surface; and (3) selecting the surface T with the greatest Hausdorff distance from the H1 and the H2; discretizing the surface T into independent points; calculating points P on the surface T and a target surface R in the corresponding correlation surface when the Hausdorff distance maximum value occurs by combining the correlation surface of the surface T; calculating the Hausdorff distance among triangular meshes; performing point-to-surface type judgment, wherein the point-to-surface types include a point-to-point type, a point-to-line type and a point-to-surface type; and performing mesh model optimization according to the point-to-surface type.

Description

technical field [0001] The invention belongs to the technical field of computer graphics, and in particular relates to an optimization method of a triangular grid model. Background technique [0002] 3D model data is an important research content in the field of computer graphics. As a new multimedia data type, 3D model data has stronger authenticity and interactivity, and has important applications in engineering design, simulation, medicine and health, and game entertainment. 3D models are generally processed as triangular mesh models. In the past few years, researchers have proposed many methods to obtain reconstructed triangular mesh models. In order to meet the subsequent processing such as deformation and compression, the method of geometric image generation is often used, that is, a two-dimensional regular grid is used to represent a triangular mesh model. Geometry was proposed by Gu Xianfeng, Hoppe et al. at the 2002 Siggraph conference. Obtaining a triangular mes...

AI Technical Summary

Problems solved by technology

However, for some areas, there will be insufficient sampling, and the detailed information cannot be accurately represented. Increasing the sampling rate will increase the amount of data and occupy a large amount of storage space.

In order to represent the triangular mesh model more accurately, Zhou Kun et al. proposed a self-adaptive sampling method, that is, on the basis of regular sampling, the sampling points are adjusted according to the distribution of parameterized vertices, so that the places where the parameterized vertices are dense are distributed as much as possible More sampling points, which can better represent the detail information, but ignore the edge information

Whether it is regular sampling or adaptive sampling, the triangular mesh model is obtained directly after sampling, and the triangular mesh model is not optimized.

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