Screened Poisson Surface Reconstruction has a good performance among the state-of-art surface reconstruction algorithms in obtaining a triangle mesh from oriented points. In order to better deal with nonuniform point clouds, Screened Poisson Surface Reconstruction uses B-spline functions with a fixed support for kernel density estimation to construct a vector field for solving the screened Poisson equation. In this paper, an adaptive bandwidth Gaussian kernel density estimator is applied, which reduces the bandwidth where the density is low, and increases the bandwidth where the density is high. Experiments show that such an estimator that makes use of both global and local points distribution can effectively remove noise and outliers in the reconstruction.

在现有的表面重建算法中，筛选的泊松表面重建在从定向点获取三角形网格方面具有良好的性能。为了更好地处理非均匀点云，屏蔽泊松曲面重建使用B样条函数并固定支持核密度估计，以构造向量场来求解屏蔽泊松方程。本文采用了一种自适应带宽高斯核密度估计器，可以减小低密度时的带宽，增加高密度时的带宽。实验表明，这种利用全局和局部点分布的估计器可以有效地消除重构中的噪声和离群值。