Image Space Rendering of Point Clouds Using the HPR Operator

The hidden point removal (HPR) operator introduced by Katz et al. [KTB07] provides an elegant solution for the problem of estimating the visibility of points in point samplings of surfaces. Since the method requires computing the three‐dimensional convex hull of a set with the same cardinality as th...

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Vydané v:Computer graphics forum Ročník 33; číslo 1; s. 178 - 189
Hlavní autori: Machado e Silva, R., Esperança, C., Marroquim, R., Oliveira, A. A. F.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Blackwell Publishing Ltd 01.02.2014
Predmet:
I.3.5 [Computer Graphics]: Computational Geometry and Object Modelling-Geometric algorithms
languages and systems
surface reconstruction rendering
visibility determination
ISSN:0167-7055, 1467-8659
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Shrnutí:The hidden point removal (HPR) operator introduced by Katz et al. [KTB07] provides an elegant solution for the problem of estimating the visibility of points in point samplings of surfaces. Since the method requires computing the three‐dimensional convex hull of a set with the same cardinality as the original cloud, the method has been largely viewed as impractical for real‐time rendering of medium to large clouds. In this paper we examine how the HPR operator can be used more efficiently by combining several image space techniques, including an approximate convex hull algorithm, cloud sampling, and GPU programming. Experiments show that this combination permits faster renderings without overly compromising the accuracy. The hidden point removal (HPR) operator introduced by Katz et al. [KTB07] provides an elegant solution for the problem of estimating the visibility of points in point samplings of surfaces. Since the method requires computing the three‐dimensional convex hull of a set with the same cardinality as the original cloud, the method has been largely viewed as impractical for real‐time rendering of medium to large clouds. In this paper we examine how the HPR operator can be used more efficiently by combining several image space techniques, including an approximate convex hull algorithm, cloud sampling, and GPU programming. Experiments show that this combination permits faster renderings without overly compromising the accuracy.
Bibliografia:ark:/67375/WNG-Q66H0DRS-7
istex:7019D1BC020161777B01112051F4962535DC6EAD
ArticleID:CGF12265
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0167-7055
1467-8659
DOI:10.1111/cgf.12265