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Robustly computing restricted Voronoi diagrams (RVD) on thin-plate models

文献类型：期刊论文

作者Wang, Pengfei1; Xin, Shiqing1; Tu, Changhe1; Yan, Dongming2; Zhou, Yuanfeng1; Zhang, Caiming1
刊名COMPUTER AIDED GEOMETRIC DESIGN
出版日期2020-05-01
卷号79页码:12
关键词Geometry processing Restricted Voronoi diagram Thin plate Tubular shape
ISSN号0167-8396
DOI10.1016/j.cagd.2020.101848
通讯作者Xin, Shiqing(xinshiqing@163.com) ; Tu, Changhe(chtu@sdu.edu.cn)
英文摘要Voronoi diagram based partitioning of a 2-manifold surface in R-3 is a fundamental operation in the field of geometry processing. However, when the input object is a thin-plate model or contains thin branches, the traditional restricted Voronoi diagrams (RVD) cannot induce a manifold structure that is conformal to the original surface. Yan et al. (2014) are the first who proposed a localized RVD (LRVD) algorithm to handle this issue. Their algorithm is based on a face-level clustering technique, followed by a sequence of bisector clipping operations. It may fail when the input model has long and thin triangles. In this paper, we propose a more elegant/robust algorithm for computing RVDs on models with thin plates or even tubular parts. Our idea is inspired by such a fact: the desired RVD must guarantee that each site dominates a single region that is topologically identical to a disk. Therefore, when a site dominates disconnected subregions, we identify those ownerless regions and re-partition them to the nearby sites using a simple and fast local Voronoi partitioning operation. For each site that dominates a tubular part, we suggest add two more sites such that the three sites are almost rotational symmetric. Our approach is easy to implement and more robust to challenging cases than the state-of-the-art approach. (C) 2020 Elsevier B.V. All rights reserved.
WOS关键词TRIANGULAR MESHES ; TESSELLATIONS ; RESOLUTION
资助项目National Natural Science Foundation of China[61772318] ; National Natural Science Foundation of China[61772016] ; National Natural Science Foundation of China[61772312] ; National Natural Science Foundation of China[61772523] ; NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization[U1609218] ; NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization[U1909210]
WOS研究方向Computer Science ; Mathematics
语种英语
WOS记录号WOS:000533516400006
出版者ELSEVIER
资助机构National Natural Science Foundation of China ; NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization
源URL[http://ir.ia.ac.cn/handle/173211/39460]  
专题模式识别国家重点实验室_三维可视计算
通讯作者Xin, Shiqing; Tu, Changhe
作者单位1.Shandong Univ, Jinan, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Pengfei,Xin, Shiqing,Tu, Changhe,et al. Robustly computing restricted Voronoi diagrams (RVD) on thin-plate models[J]. COMPUTER AIDED GEOMETRIC DESIGN,2020,79:12.
APA Wang, Pengfei,Xin, Shiqing,Tu, Changhe,Yan, Dongming,Zhou, Yuanfeng,&Zhang, Caiming.(2020).Robustly computing restricted Voronoi diagrams (RVD) on thin-plate models.COMPUTER AIDED GEOMETRIC DESIGN,79,12.
MLA Wang, Pengfei,et al."Robustly computing restricted Voronoi diagrams (RVD) on thin-plate models".COMPUTER AIDED GEOMETRIC DESIGN 79(2020):12.

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来源：自动化研究所

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