As more of our important data finds its way into the cloud, those seeking to exploit that data will seek the weakest point of entry.
随着我们重要的数据被越来越多的存储到云(云计算)里，寻求窃取那些数据的人会在最薄弱的环节下手的。
The discrete point cloud data sampling from the striation figure is common.
采样于线状图形的离散点云数据也是常见的。
Great amount time is needed to directly transmit the point cloud surfaces model with great amount data points.
由于数据量大，直接传输点云曲面需耗费大量传输时间。
Read the LIDAR point cloud data, and can be displayed.
读取LIDAR的点云数据，并且可以显示出来。
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。
On the base of the type of the point cloud, the author puts forward"T"method on the scan line data reduction, compares them with other methods of the data reduction.
鉴于激光测量机获取的扫描线点云数据类型特点，提出了T值法数据简化方法，并与其它几种数据简化方法进行了比较；
For the laser scanning data of a building fa? Ade, which is featured with huge amount of data and complex point cloud, it is difficult to extract building's feature information.
对于建筑物立面的激光扫描数据来说，具有数据量大，点云复杂等特点，提取建筑物特征信息具有一定难度。
Key of the data simplification technology is while at the same time of simplifying the data to reserve the original characteristics of point cloud data to the largest extent.
数据精简技术的关键是在精简数据的同时，最大限度地保留点云数据的原有特征。
The combined effects of various factors mainly reflected in the accuracy of point cloud data.
而各种因素的综合影响则主要反映在点云数据的精度上。
Using LS5000 3d laser scanner, we can acquire the point cloud data of the real actor's face.
利用LS 5000型三维激光扫描仪扫描真实演员人脸，可以得到其三维人脸点云数据。
Accordingly, the study of reconstruction for surface of point cloud data has also been received significant attention.
与此相应，对点云数据的曲面重构研究也引起了足够的重视。
The Faro arm moved around the object, capturing point-cloud data and depth information.
在法鲁手臂到处移动的对象，捕捉点云数据和深入的信息。
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。
As a key of airborne laser data processing, the filtering of point cloud has been an important prerequisite and research focus of data applications.
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。
After the objects are scanned the large number's original point cloud data of a great density will generate, and in which noise are randomly distributing.
物体经过扫描后，得到的大量原始点云数据一般密度很大，且其中随机分布着噪声数据。
The paper studys the problem of point cloud data precision after detailed analyzing the principle of airborne LiDAR and the characteristics of point cloud data.
本文在详细分析机载激光雷达工作原理及其点云数据特点的基础上，探讨研究点云数据的精度问题。
The grid index based on linear quadtree is used to index the point cloud data, extracting the point cloud on the block.
采用基于线性四叉树的格网索引对点云数据建立索引，对点云数据进行分块提取；
A new region-growing algorithm is presented for triangular mesh surface reconstruction from point-cloud data.
提出一种新的由点云数据生成三角网格曲面的区域增长算法。
Use car's sealing strips point cloud data, it is introduced in detail which car's sealing strips section characteristic curve extraction method with developed characteristic curve extraction module.
以汽车密封条转接头管状部分点云数据为实例，详细介绍了通过开发的特征线模块进行汽车密封条截面特征线提取的方法。
Including cross-section slice of the point cloud data points for the average effective sample obtained the spray gun spray path.
包括对点云切片截面有效数据点进行平均采样，得到喷枪在工件表面的喷涂路径；
Underground engineering analysis of settlement data USES detect discrete point method, rendering the settlement warning cloud, which on the surface for the settlement of intuitive judgments.
地下工程沉降数据通常采用分析离散检测点的方法，绘制沉降预警云图，从而对地表的沉降情况进行直观的判断。
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。
A systematic scheme is proposed to automatically extract geometric surface features from a point cloud composed of a set of unorganized three-dimensional coordinate points by data segmentation.
给出了数据分块系统性方案，即从仅含有三维坐标的散乱的点云中自动提取几何曲面特性。
Spatial 3d point cloud can be quickly captured on object surface by laser scanning, however its data volume is huge.
三维激光扫描获得的点云数据，其数据量比较大。
To improve the reverse modeling efficiency of aeroengine pipelines, a region-growing segmentation algorithm for aeroengine pipeline point cloud data is proposed based on geometric attributes.
为了提高航空发动机管路测量数据的反求建模效率，提出了一种区域增长分割算法。
Through point cloud data acquired from the building, the course of registration based ICP algorithm is provided.
通过建筑物三维激光扫描数据的采集，对基于ICP算法的点云数据配准过程进行了详细地分析。
Fig. 4 Comparison of LiDAR point cloud data and traditional optical image. (a) UAV LiDAR data;
图4激光雷达点云数据和传统光学影像数据比较。 （a）无人机激光雷达点云数据；
Fig. 4 Comparison of LiDAR point cloud data and traditional optical image. (a) UAV LiDAR data;
图4激光雷达点云数据和传统光学影像数据比较。 （a）无人机激光雷达点云数据；
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