Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Adaptive Simplification Method of 3D Mesh Model Based on Local Area Features

A technology of local area features and model adaptation, applied in biological neural network models, neural learning methods, 3D modeling, etc., to achieve the effect of maintaining detailed features and reducing triangular patches

Active Publication Date: 2021-08-10
SOUTH CHINA UNIV OF TECH
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing mesh simplification algorithm considers the geometry, topology information, color, texture and other attributes of the model to constrain the simplification process, and rarely considers the problem of adaptive simplification according to the characteristics of different regions of the model.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Adaptive Simplification Method of 3D Mesh Model Based on Local Area Features
  • Adaptive Simplification Method of 3D Mesh Model Based on Local Area Features
  • Adaptive Simplification Method of 3D Mesh Model Based on Local Area Features

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] The present invention will be further described below in conjunction with specific examples.

[0040] Such as figure 1 As shown, the self-adaptive simplification method for a 3D mesh model based on local region features provided in this embodiment includes the following steps:

[0041] 1) Obtain a local area dataset from a 3D model dataset

[0042] 1.1) Extract local area

[0043] For a 3D mesh model, first select the vertex V with the largest curvature 1 As the first seed point to extract the local area, from the vertex V 1 Departure, traverse V 1 The neighborhood vertices of , define its 1-ring neighborhood, 2-ring neighborhood vertices...and the surface composed of these vertices as a local area, when the local area contains the specified number of grid vertices or the number of iterations reaches the specified The number of M times (take 30 times) is to stop the iteration, and the extraction of a local area is completed; then select the grid vertex farthest fro...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a method for self-adaptive simplification of a three-dimensional grid model based on local area features, comprising steps: 1) constructing a local area data set from a three-dimensional model data set; 2) training an MLP classification network: using the local area data set to train a Classification network based on local area features and simplification rate; 3) Calculate vertex normal deviation threshold: define the functional relationship between the classification result and vertex normal deviation threshold, and use the classification result to calculate the vertex normal deviation threshold. The present invention proposes a local area extraction method based on the topological structure of a three-dimensional grid model, using MLP to train a classifier for regional features, and when simplifying, classify each local area and use the classification result to guide the vertices of the local area to set the normal deviation threshold, That is, different simplification termination conditions are set for local areas, which avoids setting a uniform simplification rate for the model, realizes adaptive simplification, and obtains a higher simplification rate.

Description

technical field [0001] The invention relates to the technical field of simplification of a three-dimensional grid model, in particular to an adaptive simplification method of a three-dimensional grid model based on local area features. Background technique [0002] With the development of computer graphics and the improvement of computer performance, 3D models have been widely used and researched in fields such as virtual reality, animation games, and manufacturing. The rapid development of 3D data acquisition and modeling technology has made the accuracy of 3D models higher and higher, and the amount of data has also increased rapidly, which has brought huge pressure to the computer's drawing, transmission, editing and other systems. One way to solve these problems is to simplify the 3D model. At present, the commonly used grid simplification methods mostly control the simplification process from the geometric level. By setting a global simplification rate, calculating the...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06T17/20G06T19/20G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06T17/20G06T19/20G06N3/08G06T2200/04G06V10/44G06N3/045G06F18/241
Inventor 冼楚华杨煜
Owner SOUTH CHINA UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products