Lightweight preprocessing and fast query of geodesic distance via proximity graph

Computing geodesic distance on a mesh surface efficiently and accurately is a central task in numerous computer graphics applications. In order to deal with high-resolution mesh surfaces, a lightweight preprocessing is a proper choice to make a balance between query accuracy and speed. In the prepr...

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Main Authors: Xin, Shiqing, Wang, Wenping, He, Ying, Zhou, Yuanfeng, Chen, Shuangmin, Tu, Changhe, Shu, Zhenyu
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2019
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Online Access:https://hdl.handle.net/10356/85378
http://hdl.handle.net/10220/49218
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-853782020-03-07T11:48:55Z Lightweight preprocessing and fast query of geodesic distance via proximity graph Xin, Shiqing Wang, Wenping He, Ying Zhou, Yuanfeng Chen, Shuangmin Tu, Changhe Shu, Zhenyu School of Computer Science and Engineering Proximity Graph Geodesic Distance Engineering::Computer science and engineering Computing geodesic distance on a mesh surface efficiently and accurately is a central task in numerous computer graphics applications. In order to deal with high-resolution mesh surfaces, a lightweight preprocessing is a proper choice to make a balance between query accuracy and speed. In the preprocessing stage, we build a proximity graph with regard to a set of sample points and keep the exact geodesic distance between any pair of nearby sample points. In the query stage, given two query points and , we augment the proximity graph by adding and on-the-fly, and then use the shortest path between and on the augmented proximity graph to approximate the exact geodesic path between and . We establish an empirical relationship between the number of samples and expected accuracy (measured in relative error), which facilitates fast and accurate query of geodesic distance with a lightweight processing cost. We exhibit the uses of the new approach in two applications—real-time computation of discrete exponential map for texture mapping and interactive design of spline curves on surfaces. 2019-07-09T08:22:38Z 2019-12-06T16:02:44Z 2019-07-09T08:22:38Z 2019-12-06T16:02:44Z 2018 Journal Article Xin, S., Wang, W., He, Y., Zhou, Y., Chen, S., Tu, C., & Shu, Z. (2018). Lightweight preprocessing and fast query of geodesic distance via proximity graph. Computer-Aided Design, 102, 128-138. doi:10.1016/j.cad.2018.04.021 0010-4485 https://hdl.handle.net/10356/85378 http://hdl.handle.net/10220/49218 10.1016/j.cad.2018.04.021 en Computer-Aided Design © 2018 Elsevier Ltd. All rights reserved.
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Proximity Graph
Geodesic Distance
Engineering::Computer science and engineering
spellingShingle Proximity Graph
Geodesic Distance
Engineering::Computer science and engineering
Xin, Shiqing
Wang, Wenping
He, Ying
Zhou, Yuanfeng
Chen, Shuangmin
Tu, Changhe
Shu, Zhenyu
Lightweight preprocessing and fast query of geodesic distance via proximity graph
description Computing geodesic distance on a mesh surface efficiently and accurately is a central task in numerous computer graphics applications. In order to deal with high-resolution mesh surfaces, a lightweight preprocessing is a proper choice to make a balance between query accuracy and speed. In the preprocessing stage, we build a proximity graph with regard to a set of sample points and keep the exact geodesic distance between any pair of nearby sample points. In the query stage, given two query points and , we augment the proximity graph by adding and on-the-fly, and then use the shortest path between and on the augmented proximity graph to approximate the exact geodesic path between and . We establish an empirical relationship between the number of samples and expected accuracy (measured in relative error), which facilitates fast and accurate query of geodesic distance with a lightweight processing cost. We exhibit the uses of the new approach in two applications—real-time computation of discrete exponential map for texture mapping and interactive design of spline curves on surfaces.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Xin, Shiqing
Wang, Wenping
He, Ying
Zhou, Yuanfeng
Chen, Shuangmin
Tu, Changhe
Shu, Zhenyu
format Article
author Xin, Shiqing
Wang, Wenping
He, Ying
Zhou, Yuanfeng
Chen, Shuangmin
Tu, Changhe
Shu, Zhenyu
author_sort Xin, Shiqing
title Lightweight preprocessing and fast query of geodesic distance via proximity graph
title_short Lightweight preprocessing and fast query of geodesic distance via proximity graph
title_full Lightweight preprocessing and fast query of geodesic distance via proximity graph
title_fullStr Lightweight preprocessing and fast query of geodesic distance via proximity graph
title_full_unstemmed Lightweight preprocessing and fast query of geodesic distance via proximity graph
title_sort lightweight preprocessing and fast query of geodesic distance via proximity graph
publishDate 2019
url https://hdl.handle.net/10356/85378
http://hdl.handle.net/10220/49218
_version_ 1681036313528107008