点云数据的三角剖分及计算机三维重建

为了解决直接剖分法因点云数据拓扑结构复杂出现的自交现象,提出了一种基于分治策略的三角剖分方法.首先,对原始点云数据进行平面投影并执行区域分割;其次,在每一个区域内进行直接剖分,剖分过程遵循异侧剖分准则、法向量夹角最大剖分准则、阈值距离剖分准则、最小内角最大剖分准则.最后,按照空间Delaunay剖分准则完成区域之间的连接.实验结果表明,该文提出的剖分方法对于规则曲面点云和非规则曲面点云都具有理想的剖分效果,并且执行速度快.

Triangulation and Computer Three-Dimensional Reconstruction of Point Cloud Data

In order to solve the self-intersection of point cloud data caused by complex topological structure, a triangulation method based on divide-and-conquer strategy has been proposed. Firstly, the original point cloud data are projected on a plane and partitioned into regions. Secondly, each region is partitioned directly. The partitioning process follows the criteria of lateral partitioning, maximum normal vector angle partitioning, threshold distance partitioning and maximum minimum internal angle partitioning. Finally, the connection between regions is completed according to the spatial Delaunay partition criterion. The experimental results show that the proposed method has ideal segmentation effect for both regular and irregular surface point clouds, and the execution speed is fast.