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Article: Computing geodesies on point clouds

TitleComputing geodesies on point clouds
Authors
KeywordsDijkstra's Algorithm
Geodesic Curves
Point Cloud
Square Distance Minimization
Issue Date2006
Citation
Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal Of Computer-Aided Design And Computer Graphics, 2006, v. 18 n. 3, p. 438-442 How to Cite?
AbstractGiven two points on an object represented by point cloud, we first obtain an approximately shortest path between the two points as an initial active curve by using Dijkstra's algorithm, then we use square distance minimization method to compute the active curve iteratively to be the geodesic between the two points on the point cloud. We define the objective function to be constraints of the distance between the active curve and the point cloud as well as the arc length of the active curve, and then minimize the objective function step by step by relocating the control points of the active curve until a convergence result is achieved. The method avoids triangulating or reconstructing the point cloud to be a surface model so that it is practicable for dealing with the point cloud with a huge number of scattered points.
Persistent Identifierhttp://hdl.handle.net/10722/152332
ISSN
2015 SCImago Journal Rankings: 0.197

 

DC FieldValueLanguage
dc.contributor.authorDu, Pen_US
dc.contributor.authorTu, Cen_US
dc.contributor.authorWang, Wen_US
dc.date.accessioned2012-06-26T06:37:15Z-
dc.date.available2012-06-26T06:37:15Z-
dc.date.issued2006en_US
dc.identifier.citationJisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal Of Computer-Aided Design And Computer Graphics, 2006, v. 18 n. 3, p. 438-442en_US
dc.identifier.issn1003-9775en_US
dc.identifier.urihttp://hdl.handle.net/10722/152332-
dc.description.abstractGiven two points on an object represented by point cloud, we first obtain an approximately shortest path between the two points as an initial active curve by using Dijkstra's algorithm, then we use square distance minimization method to compute the active curve iteratively to be the geodesic between the two points on the point cloud. We define the objective function to be constraints of the distance between the active curve and the point cloud as well as the arc length of the active curve, and then minimize the objective function step by step by relocating the control points of the active curve until a convergence result is achieved. The method avoids triangulating or reconstructing the point cloud to be a surface model so that it is practicable for dealing with the point cloud with a huge number of scattered points.en_US
dc.languageengen_US
dc.relation.ispartofJisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphicsen_US
dc.subjectDijkstra's Algorithmen_US
dc.subjectGeodesic Curvesen_US
dc.subjectPoint Clouden_US
dc.subjectSquare Distance Minimizationen_US
dc.titleComputing geodesies on point cloudsen_US
dc.typeArticleen_US
dc.identifier.emailWang, W:wenping@cs.hku.hken_US
dc.identifier.authorityWang, W=rp00186en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-33645773481en_US
dc.identifier.volume18en_US
dc.identifier.issue3en_US
dc.identifier.spage438en_US
dc.identifier.epage442en_US
dc.identifier.scopusauthoridDu, P=35965430600en_US
dc.identifier.scopusauthoridTu, C=7402578832en_US
dc.identifier.scopusauthoridWang, W=35147101600en_US

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