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Front. Inform. Technol. Electron. Eng.  2012, Vol. 13 Issue (6): 440-451    DOI: 10.1631/jzus.C1100324
    
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
School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China; State Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian 116024, China; 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; Department of Mathematical Sciences, Delaware State University, Dover, DE 19901, USA
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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.

Key wordsFeature detection      Neighbor supporting      Normal tensor voting      Salient measure     
Received: 01 November 2011      Published: 05 June 2012
CLC:  TP391.4  
Cite this article:

Xiao-chao Wang, Jun-jie Cao, Xiu-ping Liu, Bao-jun Li, Xi-quan Shi, Yi-zhen Sun. Feature detection of triangular meshes via neighbor supporting. Front. Inform. Technol. Electron. Eng., 2012, 13(6): 440-451.

URL:

http://www.zjujournals.com/xueshu/fitee/10.1631/jzus.C1100324     OR     http://www.zjujournals.com/xueshu/fitee/Y2012/V13/I6/440


Feature detection of triangular meshes via neighbor supporting

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: Feature detection,  Neighbor supporting,  Normal tensor voting,  Salient measure 
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