Efficient triangulation of Poisson-disk sampled point sets

Jianwei Guo; Dongming Yan; Guanbo Bao; Weiming Dong; Xiaopeng Zhang; Peter Wonka

doi:10.1007/s00371-014-0948-z

Efficient triangulation of Poisson-disk sampled point sets

Jianwei Guo, Dongming Yan, Guanbo Bao, Weiming Dong, Xiaopeng Zhang, Peter Wonka

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

10 Scopus citations

Abstract

In this paper, we present a simple yet efficient algorithm for triangulating a 2D input domain containing a Poisson-disk sampled point set. The proposed algorithm combines a regular grid and a discrete clustering approach to speedup the triangulation. Moreover, our triangulation algorithm is flexible and performs well on more general point sets such as adaptive, non-maximal Poisson-disk sets. The experimental results demonstrate that our algorithm is robust for a wide range of input domains and achieves significant performance improvement compared to the current state-of-the-art approaches. © 2014 Springer-Verlag Berlin Heidelberg.

Original language	English (US)
Pages (from-to)	773-785
Number of pages	13
Journal	The Visual Computer
Volume	30
Issue number	6-8
DOIs	https://doi.org/10.1007/s00371-014-0948-z
State	Published - May 6 2014

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This research was partially funded by National Natural Science Foundation of China (Nos. 61372168, 61172104, 61331018, and 61271431), the KAUST Visual Computing Center, and the National Science Foundation.

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Software
Computer Vision and Pattern Recognition

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10.1007/s00371-014-0948-z

Cite this

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abstract = "In this paper, we present a simple yet efficient algorithm for triangulating a 2D input domain containing a Poisson-disk sampled point set. The proposed algorithm combines a regular grid and a discrete clustering approach to speedup the triangulation. Moreover, our triangulation algorithm is flexible and performs well on more general point sets such as adaptive, non-maximal Poisson-disk sets. The experimental results demonstrate that our algorithm is robust for a wide range of input domains and achieves significant performance improvement compared to the current state-of-the-art approaches. {\textcopyright} 2014 Springer-Verlag Berlin Heidelberg.",

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AU - Guo, Jianwei

AU - Yan, Dongming

AU - Bao, Guanbo

AU - Dong, Weiming

AU - Zhang, Xiaopeng

AU - Wonka, Peter

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: This research was partially funded by National Natural Science Foundation of China (Nos. 61372168, 61172104, 61331018, and 61271431), the KAUST Visual Computing Center, and the National Science Foundation.

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Y1 - 2014/5/6

N2 - In this paper, we present a simple yet efficient algorithm for triangulating a 2D input domain containing a Poisson-disk sampled point set. The proposed algorithm combines a regular grid and a discrete clustering approach to speedup the triangulation. Moreover, our triangulation algorithm is flexible and performs well on more general point sets such as adaptive, non-maximal Poisson-disk sets. The experimental results demonstrate that our algorithm is robust for a wide range of input domains and achieves significant performance improvement compared to the current state-of-the-art approaches. © 2014 Springer-Verlag Berlin Heidelberg.

AB - In this paper, we present a simple yet efficient algorithm for triangulating a 2D input domain containing a Poisson-disk sampled point set. The proposed algorithm combines a regular grid and a discrete clustering approach to speedup the triangulation. Moreover, our triangulation algorithm is flexible and performs well on more general point sets such as adaptive, non-maximal Poisson-disk sets. The experimental results demonstrate that our algorithm is robust for a wide range of input domains and achieves significant performance improvement compared to the current state-of-the-art approaches. © 2014 Springer-Verlag Berlin Heidelberg.

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Efficient triangulation of Poisson-disk sampled point sets

Abstract

Bibliographical note

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