本文提出了一种散乱点云数据的建模新方法。
A new modeling method for scattered point cloud is presented.
为高效精确处理散乱点云数据，改进了区域生长算法。
To deal with scattered measured points effectively and exactly, an improved algorithm of region growing was presented.
散乱点云数据的测量是三维物体曲面重建的前提和基础。
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。
Measurement of 3d object to obtain its scattered points cloud data is the foundation of surface reconstruction.
提出了一种在反求工程中对散乱点云数据进行自动分割与曲面模型重构的方法。
A method of automatic segmentation and surface reconstruction of scattered data in reverse engineering was presented.
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。
After establishing the topology relationship of scattered points, the mesh surface model of point data is reconstructed by triangulation.
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。
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.
提出了一种基于散乱点云的数据预处理方法。
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。
A method of data preprocessing based on scattered point cloud was proposed.
应用推荐