This is supported by the comparison with the results of hierarchical clustering segmentation of point cloud model and K-Means clustering segmentation of mesh model.
与三维网格模型的K均值聚类分割、点云模型的谱系聚类分割的实验结果比较证实了这一点。
With its characteristics such as strong detailing ability, and simple storage, 3D point cloud model has been one of the most commonly used three-dimensional objects in CAD/CG.
点云模型由于具备表示三维细节能力强、存储简单等特点，成为CAD／CG最常用的三维物体表示模型之一。
Point cloud morphing is a topic about how to transfer a source model into a target model smoothly.
点云模型渐变研究如何将一个源点云模型平滑的变化成目标点云模型。
The point cloud segmentation is an extremely essential step in the reverse model design. The segmentation results will affect the surface fitting and the CAD model reconstruction quality directly.
数据点云分块是逆向工程中一个非常关键的环节，测量数据的分块结果将直接影响到曲面拟合及CAD模型重建的质量。
Now based on the three-dimensional reconstruction of point cloud, it is to make three-dimensional surface grid model through some algorithm.
目前基于点云的三维重建，大都是通过一些算法构造出三维表面网格模型。
Point-Based Rendering uses discrete and crowded point cloud to represent the surface of model, and it's goal is to reconstruct a continuous and equivalent surface from the point cloud.
基于点的绘制技术使用离散的三维密集点云来表征模型表面，目标是采用点元作为基本绘制单元在三维密集点云中重构出连续、视觉等价的模型表面。
We addressed the problems and solutions of converting a measured point cloud into a realistic 3D polygonal model that can satisfy high modelling and visualization demands.
将三维扫描仪测量得到的点云转换成一个实际的3D（三维）多边形模型，以满足高级建模和可视化的需要。 为此提到了转换过程中出现的所有问题和解决方法。
The high precision and reliability of the reconstruction model are reached by increasing sample density of measuring point cloud.
通过增加点云的采样密度，提高重建模型的精度和可靠性。
The results show that this point cloud registration error model and the experimental method are excellent.
结果表明点云误差传播模型正确，试验方法良好。
Because the number of complex buildings 'point cloud data is very huge, this paper has determined the suitable criterion of model simplifying through experiments using different accuracy.
针对复杂建筑物的点云数据量庞大，通过不同精度的实验确定了模型简化的适宜尺度。
Because the number of complex buildings 'point cloud data is very huge, this paper has determined the suitable criterion of model simplifying through experiments using different accuracy.
针对复杂建筑物的点云数据量庞大，通过不同精度的实验确定了模型简化的适宜尺度。
应用推荐