GBGVD: growth-based geodesic Voronoi diagrams

Given a set of generators, the geodesic Voronoi diagram (GVD) defines how the base surface is decomposed into separate regions such that each generator dominates a region in terms of geodesic distance to the generators. Generally speaking, each ordinary bisector point of the GVD is determined by two...

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Main Authors: Qi, Yunjia, Zong, Chen, Zhang, Yunxiao, Chen, Shuangmin, Xu, Minfeng, Ran, Lingqiang, Xu, Jian, Xin, Shiqing, He, Ying
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2024
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Online Access:https://hdl.handle.net/10356/174205
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1742052024-03-22T15:36:47Z GBGVD: growth-based geodesic Voronoi diagrams Qi, Yunjia Zong, Chen Zhang, Yunxiao Chen, Shuangmin Xu, Minfeng Ran, Lingqiang Xu, Jian Xin, Shiqing He, Ying School of Computer Science and Engineering Computer and Information Science Given a set of generators, the geodesic Voronoi diagram (GVD) defines how the base surface is decomposed into separate regions such that each generator dominates a region in terms of geodesic distance to the generators. Generally speaking, each ordinary bisector point of the GVD is determined by two adjacent generators while each branching point of the GVD is given by at least three generators. When there are sufficiently many generators, straight-line distance serves as an effective alternative of geodesic distance for computing GVDs. However, for a set of sparse generators, one has to use exact or approximate geodesic distance instead, which requires a high computational cost to trace the bisectors and the branching points. We observe that it is easier to infer the branching points by stretching the ordinary segments than competing between wavefronts from different directions. Based on the observation, we develop an unfolding technique to compute the ordinary points of the GVD, as well as a growth-based technique to stretch the traced bisector segments such that they finally grow into a complete GVD. Experimental results show that our algorithm runs 3 times as fast as the state-of-the-art method at the same accuracy level. Ministry of Education (MOE) Published version This work is supported by National Key R and D Program of China (2021YFB1715900), National Natural Science Foundation of China (62002190, 62272277), NSF of Shandong Province, China (ZR2020MF036), Shandong Province Higher Educational Science and Technology Program (KJ2018BAN062), Youth Innovation Science and Technology Support Program of Shandong Province Higher Education (2020KJN007) and Singapore Ministry of Education Academic Research Fund (MOE-T2EP20220-0005). 2024-03-20T08:05:36Z 2024-03-20T08:05:36Z 2023 Journal Article Qi, Y., Zong, C., Zhang, Y., Chen, S., Xu, M., Ran, L., Xu, J., Xin, S. & He, Y. (2023). GBGVD: growth-based geodesic Voronoi diagrams. Graphical Models, 129, 101196-. https://dx.doi.org/10.1016/j.gmod.2023.101196 1524-0703 https://hdl.handle.net/10356/174205 10.1016/j.gmod.2023.101196 2-s2.0-85172415481 129 101196 en MOE-T2EP20220-0005 Graphical Models © 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Computer and Information Science
spellingShingle Computer and Information Science
Qi, Yunjia
Zong, Chen
Zhang, Yunxiao
Chen, Shuangmin
Xu, Minfeng
Ran, Lingqiang
Xu, Jian
Xin, Shiqing
He, Ying
GBGVD: growth-based geodesic Voronoi diagrams
description Given a set of generators, the geodesic Voronoi diagram (GVD) defines how the base surface is decomposed into separate regions such that each generator dominates a region in terms of geodesic distance to the generators. Generally speaking, each ordinary bisector point of the GVD is determined by two adjacent generators while each branching point of the GVD is given by at least three generators. When there are sufficiently many generators, straight-line distance serves as an effective alternative of geodesic distance for computing GVDs. However, for a set of sparse generators, one has to use exact or approximate geodesic distance instead, which requires a high computational cost to trace the bisectors and the branching points. We observe that it is easier to infer the branching points by stretching the ordinary segments than competing between wavefronts from different directions. Based on the observation, we develop an unfolding technique to compute the ordinary points of the GVD, as well as a growth-based technique to stretch the traced bisector segments such that they finally grow into a complete GVD. Experimental results show that our algorithm runs 3 times as fast as the state-of-the-art method at the same accuracy level.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Qi, Yunjia
Zong, Chen
Zhang, Yunxiao
Chen, Shuangmin
Xu, Minfeng
Ran, Lingqiang
Xu, Jian
Xin, Shiqing
He, Ying
format Article
author Qi, Yunjia
Zong, Chen
Zhang, Yunxiao
Chen, Shuangmin
Xu, Minfeng
Ran, Lingqiang
Xu, Jian
Xin, Shiqing
He, Ying
author_sort Qi, Yunjia
title GBGVD: growth-based geodesic Voronoi diagrams
title_short GBGVD: growth-based geodesic Voronoi diagrams
title_full GBGVD: growth-based geodesic Voronoi diagrams
title_fullStr GBGVD: growth-based geodesic Voronoi diagrams
title_full_unstemmed GBGVD: growth-based geodesic Voronoi diagrams
title_sort gbgvd: growth-based geodesic voronoi diagrams
publishDate 2024
url https://hdl.handle.net/10356/174205
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