Efficient maximal Poisson-disk sampling and remeshing on surfaces

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.

Guo, J., Yan, D.-M., Jia, X., & Zhang, X. (2015). Efficient maximal Poisson-disk sampling and remeshing on surfaces. Computers & Graphics, 46, 72–79. doi:10.1016/j.cag.2014.09.015

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).

Elsevier BV

Computers & Graphics


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