Visibility of noisy point cloud data

Handle URI:
http://hdl.handle.net/10754/575799
Title:
Visibility of noisy point cloud data
Authors:
Mehra, Ravish; Tripathi, Pushkar; Sheffer, Alla; Mitra, Niloy J. ( 0000-0002-2597-0914 )
Abstract:
We present a robust algorithm for estimating visibility from a given viewpoint for a point set containing concavities, non-uniformly spaced samples, and possibly corrupted with noise. Instead of performing an explicit surface reconstruction for the points set, visibility is computed based on a construction involving convex hull in a dual space, an idea inspired by the work of Katz et al. [26]. We derive theoretical bounds on the behavior of the method in the presence of noise and concavities, and use the derivations to develop a robust visibility estimation algorithm. In addition, computing visibility from a set of adaptively placed viewpoints allows us to generate locally consistent partial reconstructions. Using a graph based approximation algorithm we couple such reconstructions to extract globally consistent reconstructions. We test our method on a variety of 2D and 3D point sets of varying complexity and noise content. © 2010 Elsevier Ltd. All rights reserved.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Elsevier BV
Journal:
Computers & Graphics
Conference/Event name:
Shape Modelling International (SMI) Conference 2010
Issue Date:
Jun-2010
DOI:
10.1016/j.cag.2010.03.002
Type:
Conference Paper
ISSN:
00978493
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorMehra, Ravishen
dc.contributor.authorTripathi, Pushkaren
dc.contributor.authorSheffer, Allaen
dc.contributor.authorMitra, Niloy J.en
dc.date.accessioned2015-08-24T09:26:29Zen
dc.date.available2015-08-24T09:26:29Zen
dc.date.issued2010-06en
dc.identifier.issn00978493en
dc.identifier.doi10.1016/j.cag.2010.03.002en
dc.identifier.urihttp://hdl.handle.net/10754/575799en
dc.description.abstractWe present a robust algorithm for estimating visibility from a given viewpoint for a point set containing concavities, non-uniformly spaced samples, and possibly corrupted with noise. Instead of performing an explicit surface reconstruction for the points set, visibility is computed based on a construction involving convex hull in a dual space, an idea inspired by the work of Katz et al. [26]. We derive theoretical bounds on the behavior of the method in the presence of noise and concavities, and use the derivations to develop a robust visibility estimation algorithm. In addition, computing visibility from a set of adaptively placed viewpoints allows us to generate locally consistent partial reconstructions. Using a graph based approximation algorithm we couple such reconstructions to extract globally consistent reconstructions. We test our method on a variety of 2D and 3D point sets of varying complexity and noise content. © 2010 Elsevier Ltd. All rights reserved.en
dc.publisherElsevier BVen
dc.subjectComputer graphicsen
dc.subjectLine and curve generationen
dc.subjectNoise smoothingen
dc.subjectPoint clouden
dc.subjectSurface reconstructionen
dc.subjectVisibilityen
dc.titleVisibility of noisy point cloud dataen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalComputers & Graphicsen
dc.conference.nameShape Modelling International (SMI) Conference 2010en
dc.contributor.institutionIIT Delhi, Indiaen
dc.contributor.institutionUNC, Chapel Hill, United Statesen
dc.contributor.institutionGaTech, United Statesen
dc.contributor.institutionUBC, Canadaen
kaust.authorMitra, Niloy J.en
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