Jeong Hun Im , Young Jin Park , Dong Ook Seong , Jong Sung Ha , Kwan Hee Yoo

The KIPS Transactions:PartA, Vol. 14, No. 7, pp. 435-442, Dec. 2007
10.3745/KIPSTA.2007.14.7.435,   PDF Download:

Abstract

This paper is concerned with the mesh segmentation problem that can be applied to diverse applications such as texture mapping, simplification, morphing, compression, and shape matching for 3D mesh models. The mesh segmentation is the process of dividing a given mesh into the disjoint set of sub-meshes. We propose a method for segmenting meshes by simultaneously reflecting global and local geometric characteristics of the meshes. First, we extract sharp vertices over mesh vertices by interpreting the curvatures and convexity of a given mesh, which are respectively contained in the local and global geometric characteristics of the mesh. Next, we partition the sharp vertices into the k number of clusters by adopting the k-means clustering method [29] based on the Euclidean distances between all pairs of the sharp vertices. Other vertices excluding the sharp vertices are merged into the nearest clusters by Euclidean distances. Also we implement the proposed method and visualize its experimental results on several 3D mesh models.

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