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Approximate Poisson disk sampling on mesh

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Abstract

Poisson disk sampling has been widely used in many applications such as remeshing, procedural texturing, object distribution, illumination, etc. While 2D Poisson disk sampling is intensively studied in recent years, direct Poisson disk sampling on 2-manifold surface is rarely covered. In this paper, we present a novel framework which generates approximate Poisson disk distribution directly on mesh, a discrete representation of 2-manifold surfaces. Our framework is easy to implement and provides extra flexibility to specified sampling issues like feature-preserving sampling and adaptive sampling. We integrate the tensor voting method into feature detection and adaptive sample radius calculation. Remeshing as a special downstream application is also addressed. According to our experiment results, our framework is efficient, robust, and widely applicable.

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Authors and Affiliations

  1. Graphics and Interactive Technology Lab of Dept. of Computer Science, Peking University, Beijing, 100871, China

    Bo Geng, HuiJuan Zhang, Heng Wang & GuoPing Wang

  2. The Key Lab of Machine perception and intelligent, MOE, Beijing, 100871, China

    GuoPing Wang

Authors
  1. Bo Geng
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  2. HuiJuan Zhang
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  3. Heng Wang
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  4. GuoPing Wang
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Correspondence to GuoPing Wang.

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Geng, B., Zhang, H., Wang, H. et al. Approximate Poisson disk sampling on mesh. Sci. China Inf. Sci. 56, 1–12 (2013). https://doi.org/10.1007/s11432-011-4322-8

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  • DOI: https://doi.org/10.1007/s11432-011-4322-8

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