采用移动最小二乘的平面散乱点集曲线重构

Planar Curve Reconstruction from a Set of Unorganized Points Based on Moving Least Square

针对带状分布的无序散乱点集的曲线重构问题,采用移动最小二乘法对其进行二次局部加权回归和细化点云;在迭代过程中,采用逐步减小K-邻域顶点数的策略,以兼顾计算效率和精度.对细化后的点云进行重新排序和稀疏,把无序点集有序化;然后,利用现有的B样条曲线重构技术,对点云进行重构.最后,实例验证算法的有效性.

In allusion to curve reconstruction problem from a set of unorganized points with a zonal distribution,moving least square（MLS） is used to conduct second locally weighted regression and to thin point cloud,in the iteration process of which the strategy of reducing K-neighborhood vertices gradually is adopted in order that both computation efficiency and accuracy could be taken into account.The point cloud being thinned is recorded and resparsed to make unorganized point set orderly,the the existing B-spline curve reconstruction technique is used to reconstruct the point cloud.Finally,the validity of the algorithm is proven by the case study.