In this paper, we first polygonize the scattered data points, then estimate the normal vector and curvature of each point using the local presentation of data points.
首先对获得的散乱数据点云进行多边形化，然后根据数据点局部表示对每点的法矢和曲率进行估算。
After establishing the topology relationship of scattered points, the mesh surface model of point data is reconstructed by triangulation.
建立了散乱点云数据之间的拓扑信息，对点云数据进行三角剖分重构网格曲面模型。
A method of data preprocessing based on scattered point cloud was proposed.
提出了一种基于散乱点云的数据预处理方法。
Using the tree method partitions the unordered point data, so the geometric model of the scattered data is generated.
并通过树形的空间结构完成对密集散乱点群空间分割，由此实现对散乱点群数据的几何分割。
The measurement of scattered point cloud data is the foundation of surface reconstruction of a 3d object.
散乱点云数据的测量是三维物体曲面重建的前提和基础。
In environmental monitoring system, the data transmission among each scattered monitoring point is always a difficult problem in establishing the monitoring system.
环境监控系统中各分散监控点的数据传输问题，一直是建立环境监控系统的难点。
Several problems about data pre-processing were analyzed and solved considering the original scattered point cloud, and a new iterative algorithm based on point cloud slicing was proposed.
针对扫描点云杂乱无序的特点，讨论了点云数据预处理的问题，提出了一种新的基于点云切片的数据预处理迭代算法。
Several problems about data pre-processing were analyzed and solved considering the original scattered point cloud, and a new iterative algorithm based on point cloud slicing was proposed.
针对扫描点云杂乱无序的特点，讨论了点云数据预处理的问题，提出了一种新的基于点云切片的数据预处理迭代算法。
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