A mesh meaningful segmentation algorithm using Skeleton and minima-rule

Authors:
Zhi-Quan Cheng;Kai Xu;Bao Li;Yan-Zhen Wang;Gang Dang;Shi-Yao Jin
Affiliations:
DL Laboratory, National University of Defense Technology, Changsha City, Hunan Province, P.R. China;DL Laboratory, National University of Defense Technology, Changsha City, Hunan Province, P.R. China;DL Laboratory, National University of Defense Technology, Changsha City, Hunan Province, P.R. China;DL Laboratory, National University of Defense Technology, Changsha City, Hunan Province, P.R. China;DL Laboratory, National University of Defense Technology, Changsha City, Hunan Province, P.R. China;DL Laboratory, National University of Defense Technology, Changsha City, Hunan Province, P.R. China
Venue:
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Year:
2007

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Abstract

In this paper, a hierarchical shape decomposition algorithm is proposed, which integrates the advantages of skeleton-based and minima-rule-based meaningful segmentation algorithms. The method makes use of new geometrical and topological functions of skeleton to define initial cutting critical points, and then employs salient contours with negative minimal principal curvature values to determine natural final boundary curves among parts. And sufficient experiments have been carried out on many meshes, and shown that our framework can provide more reasonable perceptual results than single skeleton-based [8] or minima-rule-based [15] algorithm. In addition, our algorithm not only can divide a mesh of any genus into a collection of genus zero, but also partition level-of-detail meshes into similar parts.