Triangular mesh model optimization method

An optimization method, triangular mesh technology, applied in 3D modeling, image data processing, instruments, etc., can solve problems such as increasing data volume, occupying storage space, and no triangular mesh model optimization

Inactive Publication Date: 2016-05-25
BEIJING UNIV OF TECH
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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 adjust

Method used

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  • Triangular mesh model optimization method

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Embodiment Construction

[0012] Such as figure 1 As shown, the optimization method of this triangular mesh model includes the following steps:

[0013] (1) Adaptive sampling based on vertex equalization: Align the incision of the original 3D grid with the boundary of the 2D square area, and tile the 3D grid in the 2D area; when resampling, according to the parameter grid The vertex distribution is adaptively sampled, so that the resampled grid points are distributed in the vertex-intensive area of ​​the parameter grid as much as possible;

[0014] (2) Calculate the Hausdorff distance H1 from each face of the original grid to the resampled grid face, and the Hausdorff distance H2 from each face of the resampled grid to the original grid face;

[0015] (3) After discretizing the surface T with the largest Hausdorff distance from H1 and H2 into independent points, combine the associated surface of surface T to calculate the point P on the surface T when the maximum Hausdorff distance occurs, and the cor...

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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...

Claims

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Application Information

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IPC IPC(8): G06T17/00
CPCG06T17/00
Inventor 孔德慧石丽娜王少帆尹宝才
Owner BEIJING UNIV OF TECH
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