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A 3D Model Segmentation Method Based on Probability Partition Merging

A technology of 3D model and probability model, applied in the field of 3D model, can solve problems such as inability to perform effective segmentation

Active Publication Date: 2019-11-08
北京三体高创科技有限公司 +1
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Problems solved by technology

However, due to the influence of the performance of the global function, these algorithms cannot be effectively segmented when the function value cannot distinguish the model.

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  • A 3D Model Segmentation Method Based on Probability Partition Merging
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  • A 3D Model Segmentation Method Based on Probability Partition Merging

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[0034] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0035] figure 1 It is a schematic flowchart of a 3D model segmentation method based on probability partition merging in an embodiment of the present invention.

[0036] A 3D model segmentation method based on probability partition merging in this embodiment includes:

[0037] Step S1 is over-segmented to form a large number of regions, and step S11 establishes a graph G(V, E) according to the triangular mesh model in the three-dimensional model, wherein, V is a vertex, E is an edge, and Dist(V i ,V j ) is the length on E; step S12 obtains said Dist(V based on weight calculation i ,V j ) to get each pair of adjacent triangles (V i ,V j ) distance; step S13 obtains the distance of two non-adjacent triangular faces acc...

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Abstract

The invention discloses a three-dimensional model segmentation method based on probability partition merging, which includes: 1) forming a large number of regions through over-segmentation, 2) aggregating the over-segmented regions, 3) training cascaded classifiers, 4) according to the The cascaded classifier described above segments the new model, merges adjacent regions, and obtains the segmentation result. Through a large number of regions, it can be ensured that the current initial segmentation boundary contains the final ideal segmentation boundary, and then, through the logistic regression model, a cascaded two-classifier is trained to determine whether to merge adjacent regions into one area. The method of the present invention is based on the theory of machine learning, and divides the triangular grid through cascading regional aggregation, and selects a suitable segmentation result according to its needs. And the validity of the segmentation method is verified in the present invention, which is beneficial to integrate features, and achieves better results for most types of models.

Description

technical field [0001] The invention relates to the field of three-dimensional models, in particular to a three-dimensional model segmentation method based on probability partition merging. Background technique [0002] The rapid development of computer technology has created a digital world that is opposed to the real world. In this virtual world, with the help of Computer Graphics (CG) technology, it is possible to create wonderful scenes that are like the real world or even exceed the real world. In such a virtual world, 3D models occupy a very important position. The 3D model retains the geometric information of objects in the real world, and after loading properties such as lighting, materials, and textures, a realistic virtual effect can be constructed. In recent years, with the development of 3D modeling technology and the popularization of 3D scanners, the way of obtaining 3D models has developed significantly in the early years. The point cloud data can be scanne...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/11G06T7/143G06T7/162G06K9/62
CPCG06T2207/20081G06F18/23213G06F18/2451G06F18/22
Inventor 吴怀宇吴挺李阳春
Owner 北京三体高创科技有限公司
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