基于方向矢量曲率估算的点云精简研究  

Point cloud reduction research based on the normal vector curvature estimation

作　　者：王莹莹[1] 

机构地区：[1]上海理工大学机械工程学院,上海200093

出　　处：《信息技术》2015年第6期15-18,共4页Information Technology

基　　金：国家自然科学基金资助项目(51475309)

摘　　要：逆向工程获得的大量散乱点云数据,不利于后续曲面重构工作,因此需要进行点云精简。文章利用包围盒法分割原始点云数据,确定K邻域的中心点并搜索K邻域点,基于方向矢量曲率计算方法估算曲率,并采用曲率精简原则精简点云。实例证明,该方法对于大量点云精简有明显效果。In the reverse engineering,a large and scattered point cloud data take a lot of difficulties to the surface reconstruction. Therefore,it is necessary to condense the point cloud. This paper uses enveloping box method to divide the point cloud,then search the K neighborhood based on its central point. The curvature is accurately estimated based on the normal vector. It condenses the point cloud based on the curvature estimation principle. An example shows that this method is effective in the point cloud reduction.

关 键 词：逆向工程 点云精简 包围盒 方向矢量 曲率 

分 类 号：TP391.7[自动化与计算机技术—计算机应用技术]