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。
This complicates the estimation of local point cloud 3D features.
这使得3D点云特征估计变得复杂。
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。
Then the modified point cloud was optimized with a curve fitting method by moving window.
再通过移动窗口曲面拟合，对结果进一步优化。
Based on precisely matching of point cloud, this paper proposes an improved ICP algorithm.
针对点云精确匹配，提出一种改进的ICP算法。
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。
Airborne lidar point cloud filtering is the key of acquiring DSM and DEM with high precision.
机载激光点云数据滤波是获取高精度数字表面模型和数字高程模型的关键。
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。
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；
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。
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。
In this paper, point cloud getting theory, point cloud index method and point cloud filter method are concerned.
本文在点云获取理论、点云索引方法、点云滤波等方面进行了较为深入的研究。
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。
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。
There is noise and defective data on the 3d scanning point cloud. A robust mesh reconstruction algorithm is proposed.
由于3维扫描点云通常存在噪音和缺失数据，提出了一种鲁棒的点云网格重建算法。
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；
This paper proposes a geometry image representation based progressive transmission of point cloud surface on the network.
文章提出了基于几何图像表示的点云曲面网络渐进传输方法。
Finally, NURBS surface is fitted by point cloud of the blade and the cylinder surfaces are fitted by point cloud of gauges.
最后，分别拟合叶片点云和量规点云为NURBS曲面和圆柱体曲面。
Through the segmentation of the spatial box bounded by point cloud, efficient extraction of boundary information is implemented.
通过对点云数据进行空间三维划分，实现了边界信息的高效提取。
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。
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。
Registration algorithms for 3-d point cloud are investigated, given the unwrapped phase map computed based on phase measurement profilometry.
针对基于相位测量轮廓术得到的三维数据点，研究了三维点云配准算法。
With utilization of DR-CT series 3D scan digitizer, we can scan the surface of object rapidly, as well as acquire high density & quality point cloud.
采用DR-CT系列三维扫描仪，可以迅速的对物体面形进行扫描，获取高密度、高质量的扫描点云。
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。
An optimization method was presented for best-fitting of measurement point cloud to the complex surfaces, which consists of rough matching and accurate matching.
针对复杂曲面类零件加工余量分析过程中的测量数据匹配问题，提出通过初始匹配和精确匹配来实现曲面测量数据的最佳匹配。
To outline the silhouette of point cloud or mark some special signs on it, a novel approach for creating curves on point cloud with free-hand sketch is presented.
为了勾勒点云的骨架或在点云上标记符号，提出一种基于手绘的点云表面曲线构造方法。
The main problems in point cloud segmentation methods were pointed out, and the description and evaluation of point cloud segmentation in related fields were conducted.
指出了目前点云模型分割技术方法中存在的主要问题；分类介绍和评价了点云分割在相关应用中的研究工作；
The main problems in point cloud segmentation methods were pointed out, and the description and evaluation of point cloud segmentation in related fields were conducted.
指出了目前点云模型分割技术方法中存在的主要问题；分类介绍和评价了点云分割在相关应用中的研究工作；
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