改进的点云数据三维重建算法

Improved Three-Dimensional Reconstruction Algorithm for Point Cloud Data

泊松算法在重建时物体边缘容易产生未封闭的曲面,最终建成的物体存在表面粗糙、孔洞等问题。基于此,提出一种改进的三维点云重建算法。该方法首先用统计滤波器对点云简化去噪,消除重建表面的锯齿状现象;然后建立点云间拓扑结构,对点云法向量进行法向重定向,以减少法向指向的二义性;最后将具有磁盘拓扑结构的点云映射到平面,将二维三角剖分方法应用于平面参数化,给二维点提供三角形连通性,并将其传输回三维点云形成网格曲面。经过实验验证,该方法可以有效地去除噪声点,构建更加规则的三角形网格,并能有效地去除伪封闭曲面,明显改善带孔洞的表面点云重建效果且重建时间降低。

The original Poisson surface reconstruction algorithm can easily produce an unclosed surface at the edge,resulting in the surface of the final object being rough with holes.This paper proposes an improved threedimensional algorithm for reconstructing surfaces from point clouds.First,the method employs a statistical filter to simplify the denoising of the considered point clouds and eliminates the jagged phenomenon of the reconstructed surface.Then,a topological structure of point clouds is established,and the point-cloud normal vector is normally redirected to reduce the ambiguity of the normal direction.Finally,the point cloud with the disk topological structure is mapped to the plane,the two-dimensional triangulation method is applied to the plane parameterization,the triangle connectivity is provided to the two-dimensional points,and the two-dimensional points are transmitted back to the three-dimensional point cloud to form a mesh surface.The experimental results demonstrate that the method can effectively remove noise points,construct a more regular triangle mesh,and effectively remove the pseudo-enclosed surface.The surface point-cloud reconstruction effect with holes is clearly improved,and the reconstruction time is reduced.