词汇“point clouds”的读音、翻译、用法及例句

点云

Oort clouds───奥尔特云

point count───计点法

point counts───计点法

point groups───[晶体][数]点群（等于symmetryclass）

rain clouds───[气象]雨云

pendant clouds───管状云

Oort cloud───奥尔特云

Secondly, the laser propagation rule in the underground air and error influencing factors of scanning point clouds were studied systematically.───第二，研究激光在井下空气中的传播规律及扫描点云数据的误差影响因素。

rotation transformation between the point clouds is obtained by the knowledge of the vision geometry and the image information, while their translation is acquired by our improved ICP algorithm.───点云间的旋转变换是利用视觉几何知识由同轴相机在不同扫描站点下拍摄的图像直接获得，而平移变换是由本文提出的改进ICP算法得到。

object of post-scanning data processing is to reconstruct surface models from 3D point clouds.───扫描数据处理的物体将重建来自 3D立体点云的表面的模型。

In elevation data stored in form of point clouds, triangles are first formed, then treated as are those of the triangular terrain models.───在以格子点型式储存的高度资料中，三角形最常被使用，然后针对所产生的图形作讨论。

The point clouds coming from neighbor scan station are automatic registered to combine a uniform model.───首先，对相邻扫描站的激光点云自动拼接，生成统一的点云模型。

Firstly, all the pairwise points are searched by taking the curvature of point clouds as the registration relationship.───首先以点云的曲率为联系特征，搜索配准点云的匹配对集合；

Due to physical limits, a three-dimensional laser scanning can’t acquire all the data object, so to scanning point clouds for stitching.───由于物理上的一些限制，一次三维激光扫描不能获取扫描物体的全部数据，因此要对扫描点云进行拼接。

An algorithm for reconstructing surfaces from point clouds with noises and outliers acquired with a 3D scanner was presented.───针对三维扫描获取的带噪声和离群点的点云数据，提出了隐式曲面重建算法。

So, multi-view point clouds registration algorithm is necessary to be studied.───所以，本文对多视点云拼接算法进行了研究。

In order to extract the internal and external surface point clouds of the turbine blade with high accuracy, a contour tracing method based on the 3D-ICT images of the turbine blade is proposed.

This paper researches and realizes two algorithms of point clouds segmentation-the direct segmentation method based on planarity and the surface segmentation method based on logarithmic normal vector.