用于点云曲面重构的数据精简方法研究  

Research on data simplification for point cloud in surface reconstruction

作　　者：李珂珍[1] 娄小平[1] 吕乃光[1] 

机构地区：[1]北京信息科技大学光电信息与通信工程学院,北京100192

出　　处：《北京机械工业学院学报》2009年第1期17-20,共4页Journal of Beijing Institute of Machinery

基　　金：国家自然科学基金(50675015);北京市重点实验室(机电系统测控)开放课题(82073011)

摘　　要：数据精简是进行曲面重构的重要内容。通过分析现有精简方法的不足,采用了根据曲率变化对原始散乱点云进行精简的方法,重点研究了散乱点云的空间划分、邻域搜索、曲率估算和曲率精简原则。对具有不同特征的测量数据进行了精简分析,实验结果表明该方法得到了更合理的精简效果。Data simplification is an important part of surface reconstruction. Through analyzing the shortcomings of existing data simplification methods, a simplification method based on curvature variance of original scattered point cloud is adopted. This method emphasizes on the algorithms for spatial partition, neighborhood searching, curvature estimation and the principles of simplification. Through testing and analyzing some measured data with different characteristics, the results show that the algorithms achieve more reasonable effect of simplification.

关 键 词：曲面重构 空间划分 曲率估算 数据精简 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]