Feature detection of triangular meshes via neighbor supporting

Xiao-chao WANG; Jun-jie CAO; Xiu-ping LIU; Bao-jun LI; Xi-quan SHI; Yi-zhen SUN

doi:10.1631/jzus.C1100324

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Feature detection of triangular meshes via neighbor supporting

Computer & Automation | Updated：2022-12-09

- Feature detection of triangular meshes via neighbor supporting
- Feature detection of triangular meshes via neighbor supporting
- Frontiers of Information Technology & Electronic Engineering Vol. 13, Issue 6, Pages: 440-451(2012)
- Affiliations：
  
  1.School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China
  2.State Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian 116024, China
  3.State Key Laboratory of Structural Analysis for Industrial Equipment, School of Automotive Engineering, Faculty of Vehicle Engineering and Mechanics, Dalian University of Technology, Dalian 116024, China
  4.Department of Mathematical Sciences, Delaware State University, Dover, DE 19901, USA
- Author bio：
  
  [ "Xiao-chao WANG, E-mail: wangxiaochao18@gmail.com" ]
  Xiu-ping LIU, E-mail: xpliu@dlut.edu.cn
- Funds：
- DOI：10.1631/jzus.C1100324
  CLC： TP391.4
- Received：01 November 2011，
  
  Revised：2012-;5-;4，
  
  Published：2012-06
- Accepted：
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Xiao-chao WANG, Jun-jie CAO, Xiu-ping LIU, et al. Feature detection of triangular meshes via neighbor supporting[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(6): 440-451.
DOI：

Xiao-chao WANG, Jun-jie CAO, Xiu-ping LIU, et al. Feature detection of triangular meshes via neighbor supporting[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(6): 440-451. DOI： 10.1631/jzus.C1100324.

摘要

Abstract

We propose a robust method for detecting features on triangular meshes by combining normal tensor voting with neighbor supporting. Our method contains two stages: feature detection and feature refinement. First

the normal tensor voting method is modified to detect the initial features

which may include some pseudo features. Then

at the feature refinement stage

a novel salient measure deriving from the idea of neighbor supporting is developed. Benefiting from the integrated reliable salient measure feature

pseudo features can be effectively discriminated from the initially detected features and removed. Compared to previous methods based on the differential geometric property

the main advantage of our method is that it can detect both sharp and weak features. Numerical experiments show that our algorithm is robust

effective

and can produce more accurate results. We also discuss how detected features are incorporated into applications

such as feature-preserving mesh denoising and hole-filling

and present visually appealing results by integrating feature information.

关键词

Keywords

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