曲面编辑是点云处理不可缺少的研究内容。
Surface editing is indispensable in point-based data treatment.
最后，也是最重要的一点，云计算可以加快摩尔定律所预测的处理速度并且让AI的应用狭窄的子科目协同合作。
Third, and most significantly, cloud computing both turbocharges Moore's Law processing speeds and enables those narrow AI subdisciplines to communicate and work in concert.
介绍了逆向工程的基本概念，基于RE技术上的三维建模方法：数据采集、点云数据处理、三维模型重建。
Introduces the basic conception of the reverse engineering and three-dimensional modeling method based re technology: data gathering, cloud data processing and three-dimensional model rebuilding.
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.
后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。
The object of post-scanning data processing is to reconstruct surface models from 3D point clouds.
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.
对反求工程中的点云数据处理，给出一种基于特征的区域分割法来划分点云，为后续曲面拟合提供有利条件。
For dealing with the cloud data in reverse engineering, one region-division method which based on character is presented to divide up cloud data, this provides advantage to the later surface fitting.
接着重点研究了激光测距的原理，激光扫描的现状、原理和设计和对点云的处理。
Then, we emphasize the principle of laser telemeter, the actuality, the principle, the design of laser scanning and the processing to cloud of points.
“点云”数据的预处理和曲面重建技术是反求工程的关键技术，是产品CAD模型建立的前提。
Preprocessing of "points cloud" data and surface reconstruction are the critical technology of reverse engineering and are the premises of building product CAD model.
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.
目前，对点云数据后处理算法的研究还不多。
This paper focuses on the post-processing algorithm of urban scene range images.
曲面内腔类零件的反求有别于轮廓外形的反求，主要体现在数据采集的方法，点云的处理，特征点的提取以及曲线的拟合。
The reverse of lumen part is different from outline, such as collect data method, treat with point, pick up feature point and curve fitting.
对于翼型后缘等物面边界以及远场边界，提出了适合点云结构的边界条件处理方法。
Appropriate techniques are proposed for clouds of points to deal with the far field and wall boundary conditions.
作为机载激光雷达数据处理的关键环节，激光雷达点云滤波一直是数据应用的重要前提和研究热点。
As a key of airborne laser data processing, the filtering of point cloud has been an important prerequisite and research focus of data applications.
主要研究内容包括：数据采集系统设计、图像预处理、滤波方法的选择及其算法、点云生成、三维CAD模型重构。
The main content includes the design of original data collecting system, Image preprocessing, selection and algorithm of filtering method, points cloud creating, reconstruction of 3d CAD model.
由于曲面变分比曲率更适用于反映点云形体表面的性质且计算速度较快，因此该算法更适于处理点云，且具有一定的鲁棒性。
Because the surface variation is more applicable to reflect the properties of point-sample surface than curvature and faster to compute, it is more applicable to deal with point cloud and robust.
总之，本文以航空LIDAR点云数据为基础，在无其他辅助数据的情况下，采用数字图像处理技术，实现了基于航空LIDAR点云数据提取城市地区建筑物的目标。
In a word, this paper based on the airborne LIDAR points cloud data achieves the extraction of urban building by using digital image processing technique without any assistance data.
多站扫描点云的配准、拼接，如果在单站点云经过扇形网格法处理后进行，会更快速高效。
Multi-station scanning of point cloud registration and stitching would be more quickly and efficiently, if the site goes through the fan in a single grid after treatment.
点云数据拼接在逆向工程、计算机视觉、医学图像处理等方面有着十分广泛的应用。
Point-clouds registration is widely applied in reverse-engineering, computer vision and medical imaging, etc.
点云数据拼接在逆向工程、计算机视觉、医学图像处理等方面有着十分广泛的应用。
Point-clouds registration is widely applied in reverse-engineering, computer vision and medical imaging, etc.
应用推荐