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Feature sensitive re-sampling of point set surfaces with Gaussian spheres


Miao, Yong-Wei; Bösch, Jonas; Pajarola, Renato; Gopi, M; Feng, Jie-Qing (2012). Feature sensitive re-sampling of point set surfaces with Gaussian spheres. Science China Information Sciences, 55(9):2075-2089.

Abstract

Feature sensitive simplification and re-sampling of point set surfaces is an important and challenging issue for many computer graphics and geometric modeling applications. Based on the regular sampling of the Gaussian sphere and the surface normals mapping onto the Gaussian sphere, an adaptive re-sampling framework for point set surfaces is presented in this paper, which includes a naive sampling step by index propagation and a novel cluster optimization step by normalized rectification. Our proposed re-sampling scheme can generate non-uniformly distributed discrete sample points for the underlying point sets in a feature sensitive manner. The intrinsic geometric features of the underlying point set surfaces can be preserved efficiently due to our adaptive re-sampling scheme. A novel splat rendering technique is adopted to illustrate the efficiency of our re-sampling scheme. Moreover, a numerical error statistics and surface reconstruction for simplified models are also given to demonstrate the effectiveness of our algorithm in term of the simplified quality of the point set surfaces.

Abstract

Feature sensitive simplification and re-sampling of point set surfaces is an important and challenging issue for many computer graphics and geometric modeling applications. Based on the regular sampling of the Gaussian sphere and the surface normals mapping onto the Gaussian sphere, an adaptive re-sampling framework for point set surfaces is presented in this paper, which includes a naive sampling step by index propagation and a novel cluster optimization step by normalized rectification. Our proposed re-sampling scheme can generate non-uniformly distributed discrete sample points for the underlying point sets in a feature sensitive manner. The intrinsic geometric features of the underlying point set surfaces can be preserved efficiently due to our adaptive re-sampling scheme. A novel splat rendering technique is adopted to illustrate the efficiency of our re-sampling scheme. Moreover, a numerical error statistics and surface reconstruction for simplified models are also given to demonstrate the effectiveness of our algorithm in term of the simplified quality of the point set surfaces.

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2 citations in Web of Science®
2 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Date:2012
Deposited On:29 Jan 2013 08:02
Last Modified:05 Apr 2016 16:25
Publisher:Springer
ISSN:1674-733X
Publisher DOI:https://doi.org/10.1007/s11432-012-4637-0
Other Identification Number:merlin-id:7879

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