Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/85378
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dc.contributor.authorXin, Shiqingen
dc.contributor.authorWang, Wenpingen
dc.contributor.authorHe, Yingen
dc.contributor.authorZhou, Yuanfengen
dc.contributor.authorChen, Shuangminen
dc.contributor.authorTu, Changheen
dc.contributor.authorShu, Zhenyuen
dc.date.accessioned2019-07-09T08:22:38Zen
dc.date.accessioned2019-12-06T16:02:44Z-
dc.date.available2019-07-09T08:22:38Zen
dc.date.available2019-12-06T16:02:44Z-
dc.date.issued2018en
dc.identifier.citationXin, 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.2018.04.021en
dc.identifier.issn0010-4485en
dc.identifier.urihttps://hdl.handle.net/10356/85378-
dc.description.abstractComputing 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.en
dc.language.isoenen
dc.relation.ispartofseriesComputer-Aided Designen
dc.rights© 2018 Elsevier Ltd. All rights reserved.en
dc.subjectProximity Graphen
dc.subjectGeodesic Distanceen
dc.subjectEngineering::Computer science and engineeringen
dc.titleLightweight preprocessing and fast query of geodesic distance via proximity graphen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen
dc.identifier.doi10.1016/j.cad.2018.04.021en
item.grantfulltextnone-
item.fulltextNo Fulltext-
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