摘要
针对复杂自由曲面三维扫描数据多为离散点的特点,提出了一种隐式曲面重建算法,它能满足从大量离散点云数据中快速准确地建立曲面的需求。通过选择合适的形状函数,该算法可以准确描述尖锐特征比如边和角。方法是首先用八叉树细分方法来进行离散点云数据分组,然后用分段的二次函数来捕捉每组数据的局部形状,用单位分割法来组合局部的形状函数。应用实例表明,该算法可以对离散点云数据进行快速、准确、自适应的曲面重建。如果离散点云模型有指定的精度,那么隐式曲面重建算法的处理时间取决于该模型的几何复杂性和细分程度。
According to the characteristics of 3D scanner data of complicated free -form surface, an implicit sugrace reconstruction algorithm for the scattered points was presented.The algorithm was designed to meet these requirements for rapidly and accurately creating su^Caces from scattered point cloud data, and in particular the algorithm can accurately represent sharp features such as edges and corners by selecting appropriate shape functions. In the algorithm, creates an octree-based subdivision of the scattered point cloud data, captures the local shape of the points at each cell with piecewise quadratic functions, and blends together these local shape functions with the partition of unity method. Application instances demonstrate that the algorithm is capable of providing a fast, accurate, and adaptive reconstruction of complex shapes from scattered point cloud data Given a point set model processed by the implicit surface reconstruction algorithm with a specified accuracy, the computational time depends on the geometric complexity of the model and the degree of subdivision.
出处
《机械设计与制造》
北大核心
2014年第12期176-178,共3页
Machinery Design & Manufacture
基金
山东省自然科学基金项目(ZR2010EL002)
关键词
离散数据
曲面重建
形状函数
单位分割
Scattered Point
Surface Reconstruction
Shape Function
Partition of Unity
