Efficient maximal Poisson-disk sampling and remeshing on surfaces

Jianwei Guo; Dongming Yan; Xiaohong Jia; Xiaopeng Zhang

doi:10.1016/j.cag.2014.09.015

Efficient maximal Poisson-disk sampling and remeshing on surfaces

Jianwei Guo, Dongming Yan, Xiaohong Jia, Xiaopeng Zhang

Computer, Electrical and Mathematical Sciences and Engineering

Research output: Contribution to journal › Article › peer-review

39 Scopus citations

Abstract

Poisson-disk sampling is one of the fundamental research problems in computer graphics that has many applications. In this paper, we study the problem of maximal Poisson-disk sampling on mesh surfaces. We present a simple approach that generalizes the 2D maximal sampling framework to surfaces. The key observation is to use a subdivided mesh as the sampling domain for conflict checking and void detection. Our approach improves the state-of-the-art approach in efficiency, quality and the memory consumption.

Original language	English (US)
Pages (from-to)	72-79
Number of pages	8
Journal	Computers & Graphics
Volume	46
DOIs	https://doi.org/10.1016/j.cag.2014.09.015
State	Published - Feb 2015

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
General Engineering
Human-Computer Interaction

Access to Document

10.1016/j.cag.2014.09.015

Cite this

@article{7d7e1cf39ef646a9aaa40e8364caf627,

title = "Efficient maximal Poisson-disk sampling and remeshing on surfaces",

abstract = "Poisson-disk sampling is one of the fundamental research problems in computer graphics that has many applications. In this paper, we study the problem of maximal Poisson-disk sampling on mesh surfaces. We present a simple approach that generalizes the 2D maximal sampling framework to surfaces. The key observation is to use a subdivided mesh as the sampling domain for conflict checking and void detection. Our approach improves the state-of-the-art approach in efficiency, quality and the memory consumption.",

author = "Jianwei Guo and Dongming Yan and Xiaohong Jia and Xiaopeng Zhang",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: We would like to thank the anonymous reviewers for their suggestive comments. This work was partially funded by the National Natural Science Foundation of China (61372168, 11201463, 61271431, and 61331018), and the KAUST Visual Computing Center the KAUST Visual Computing Center, and the open funding project of the State Key Laboratory of Virtual Reality Technology and Systems, Beihang University (Grant No. BUAA-VR-14KF-10).",

year = "2015",

month = feb,

doi = "10.1016/j.cag.2014.09.015",

language = "English (US)",

volume = "46",

pages = "72--79",

journal = "Computers & Graphics",

issn = "0097-8493",

publisher = "Elsevier Limited",

}

TY - JOUR

T1 - Efficient maximal Poisson-disk sampling and remeshing on surfaces

AU - Guo, Jianwei

AU - Yan, Dongming

AU - Jia, Xiaohong

AU - Zhang, Xiaopeng

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: We would like to thank the anonymous reviewers for their suggestive comments. This work was partially funded by the National Natural Science Foundation of China (61372168, 11201463, 61271431, and 61331018), and the KAUST Visual Computing Center the KAUST Visual Computing Center, and the open funding project of the State Key Laboratory of Virtual Reality Technology and Systems, Beihang University (Grant No. BUAA-VR-14KF-10).

PY - 2015/2

Y1 - 2015/2

N2 - Poisson-disk sampling is one of the fundamental research problems in computer graphics that has many applications. In this paper, we study the problem of maximal Poisson-disk sampling on mesh surfaces. We present a simple approach that generalizes the 2D maximal sampling framework to surfaces. The key observation is to use a subdivided mesh as the sampling domain for conflict checking and void detection. Our approach improves the state-of-the-art approach in efficiency, quality and the memory consumption.

AB - Poisson-disk sampling is one of the fundamental research problems in computer graphics that has many applications. In this paper, we study the problem of maximal Poisson-disk sampling on mesh surfaces. We present a simple approach that generalizes the 2D maximal sampling framework to surfaces. The key observation is to use a subdivided mesh as the sampling domain for conflict checking and void detection. Our approach improves the state-of-the-art approach in efficiency, quality and the memory consumption.

UR - http://hdl.handle.net/10754/564027

UR - https://linkinghub.elsevier.com/retrieve/pii/S0097849314001034

UR - http://www.scopus.com/inward/record.url?scp=84908374946&partnerID=8YFLogxK

U2 - 10.1016/j.cag.2014.09.015

DO - 10.1016/j.cag.2014.09.015

M3 - Article

SN - 0097-8493

VL - 46

SP - 72

EP - 79

JO - Computers & Graphics

JF - Computers & Graphics

ER -

Efficient maximal Poisson-disk sampling and remeshing on surfaces

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this