面向非均匀采样点集的3维表面重建算法

Three-dimensional surface reconstruction algorithm for non-uniform sampling points

针对非均匀采样点集,提出一种改进的3维表面重建方法。该方法将整个点集进行空间划分,缩小近邻点的搜索范围,减少搜索时间;在确定近邻点时,先计算几何近邻点,然后通过求方向性点并构造最小生成树的方法,确定拓扑近邻点;最后通过将拓扑近邻点投影到局部切平面上,利用约束条件对投影点进行三角剖分,并将剖分得到的顶点连接关系映射到3维空间中,实现3维表面重建。实验结果表明,改进后的算法运行效率高、重建效果好、广泛适用于非均匀采样点集的表面重建。

An improved 3D surface reconstruction method is proposed for non-uniform sampling points. The method performs spatial partitioning for an entire set of points, in order to reduce the search range of neighbor points and decrease the search time. For searching topological neighbor points, geometric neighbor points are calculated, and Minimum Spanning Trees are constructed by finding directional points. After projecting topological neighbor points onto local tangent planes, constrained triangulation is carried out for the projected points. Then the connection of projected points is mapped directly back onto 3D space. As a result, the 3D surface is reconstructed successfully. The experimental results show that the improved algorithm is efficient, has good reconstruction effects, and can widely be used for surface reconstruction of non-uniform sampling points.