Efficient maximal Poisson-disk sampling and remeshing on surfaces

• A simple algorithm for maximal Poisson-disk sampling and remeshing one triangular mesh surfaces.
• Efficient local conflict checking without any 3D grid, using a subdivided mesh as the main structure to track empty regions.
• A local clustering-based approach for mesh extraction, and a mesh optimization strategy for high quality remeshing.

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.

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