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General Information
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2013 Vol.3(5): 453-457 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.359

Mesh Decomposition Using Skeleton and Fuzzy Clustering

Zhijing Wu and Shuangjiu Xiao
Abstract—As 3D models are used more and more in various applications, model decomposition acts as an important step for model understanding and can be used as a pre-processing step for different applications. This paper presents a mesh decomposition method based on skeleton. In recent years, a lot of work has been done to decompose polygon meshes to sub-meshes. No standard for the result, but the aim is to get reasonable sub-meshes and keep the boundaries between them fine. In this paper, we propose a mesh decomposition algorithm using skeleton and fuzzy clustering. Our method uses the skeleton of the mesh as the base to automatically get the meaningful components without over-segmentation and keeps a fine boundary using fuzzy clustering.

Index Terms—Mesh decomposition, skeleton extraction, fuzzy clustering.

The authors are with the School of Software, the Shanghai Jiao Tong University, Shanghai, 200240 China (e-mail: wuzhijingmichal@ sjtu.edu.cn, xsjiu99@cs.sjtu.edu.cn).


Cite:Zhijing Wu and Shuangjiu Xiao, "Mesh Decomposition Using Skeleton and Fuzzy Clustering," International Journal of Machine Learning and Computing vol.3, no. 5, pp. 453-457, 2013.

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