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- Scattered Points Cloud 散乱点云
- scattered point cloud 散乱点云
- Geomagic Qualify processes point cloud data from a 3D scanner. Geomagic Qualify可以处理从3D扫描仪里得到的点云数据。
- The question then is how to draw the best line through the scattered points. 接下来的问题是如何通过散布的点子画出最佳线。
- An algorithm speedily building TIN of scattered point set is presented. 该文提出了一种针对散乱点集的快速生成TIN的算法。
- The point cloud exists, but no particles are emitted on the first frame. 虽然点云已经存在，但是在第一帧并没有粒子发射出来。
- A region-growing algorithm was proposed to reconstruct triangular meshes from unorganized point cloud. 摘要提出一种对无规则点云进行三角网格重构的区域增长算法。
- By delaminating for scattered points, the paper applies video 3D wavelet transform to scattered points. 通过时散乱点的分层处理，将图像视频的三维小波变换应用于散乱点。
- By delaminating for scattered points,the paper applies video 3D wavelet transform to scattered points. 通过对散乱点的分层处理,将图像视频的三维小波变换应用于散乱点。
- When you emit particles from an element, you create a set of points called a point cloud. 当用户从一个元件发射粒子时，用户创建了一群点称之为点云。
- You can have any number of point clouds in a scene. 当发射粒子时，在场景中可以有多个点云存在。
- Based on the distribution property of scattered points, two spatial index methods, GRID and KD-Tree, are put forward to generate regular grid DTM. 该文针对离散点的空间分布特性 ,给出了基于网格分块和KD -Tree两种空间索引技术的规则格网内插方法。
- This shader defines each particle within the volume so that the point cloud doesn't look like a single volumetric mass. 这个阴影组的功能是在某个体积内确定每个粒子以便使点云渲染的时候不至于象一个单独的体积块。
- To generate regular grid digital terrain model (DTM) from scattered points, the key problem is to improve the efficiency of searching neighbor points. 从离散点内插规则格网数字地形模型 (DTM)方法的关键是如何提高待插点周围数据的搜索效率。
- LIDAR data are new data source,and they generate a high spatial resolution "point cloud". 激光雷达(LIDAR)数据是一种新型数据源,它产生的是高密度点云数据。
- A general algorithm of triangulating arbitrary planar polygonal domain and scattered point set is presented. 提出了一个适用于任意平面多边形区域及散乱点集的通用三角化算法。
- The Particle Volume Cloud shader renders the point cloud's bounding box as a volume. 粒子体积云材质节点是把点云的边界框内的区域作为一个体积来进行渲染。
- This method can triangulate the point cloud, reduce it and smooth it.Finally can get the high-quality fitting curve. 该方法能有效地对点云数据进行三角剖分、精简、平滑去噪处理等操作，并能最终得到满足要求的拟合曲线。
- It is necessary to triangulate the point cloud in reverse engineering and rapid prototyping. 点云数据三角化处理是逆向工程及快速原型领域中不可缺少的环节。
- In this paper, two spatial index methods, GRID and R-tree, are introduced to detect the duplication of scattered points and the intersection of contours. 分别探讨了基于格网分块索引重复点检查和基于R树索引等高线相交检查两种方法。
