您要查找的是不是：
- unordered point cloud 无序点云
- 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 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。
- 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。
- 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。
- 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。
- 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。
- Direct fitting surface with point cloud data obtained from autobody scanning is difficult. 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。
- This automatically creates a point cloud and sets up the node and compound connections in the ICE Tree that are needed to emit particles. 这样的操作将自动建立一个点云，并同时在ICE树中创建一套连接好的节点组，这些是发射粒子最基本的节点组。
- These goal positions are determined via a generalized shape matching of an undeformed rest state with the current deformed state of the point cloud. 这些目标位置通过一个通用的无变形的静止状态和点云的当前变形状态之间的形状匹配来决定。
- The point cloud is displayed in UGII as a UDO object based on the development tool of UGII and the pure virtual function of the C++. 摘要基于UGII系统的二次开发工具及C++的纯虚函数，实现了作为UDO对象的海量数据点在UGII中的显示技术。
- This method has been validated through different examples, using the autobody point cloud data obtained from the ATOS measurement equipment. 并结合ATOS测量设备得到的车身曲面点云数据，给出不同的实例，证明了该方法的有效性。
- If the point cloud is already polygonized, you must confirm to continue creating a new polygonization (and destroy the existing one). 如果点云已被多边形化，你必须确认继续创建一个新的多边形（破坏存在的多边形）。
- By default, they're small yellow points. You'll also notice a bounding box around the particles to indicate that the point cloud is selected. 在默认的情况下，发射出来的粒子是黄色的点。同时有一个边界盒子围绕在粒子群周围标志着粒子当前为选择状态。
- We use least squre method to form conicoid mathematic model and fit the point cloud which has been grouped by octree subdivision method. 应用最小二乘法建立二次曲面的数学模型，对于已用八叉树分组的点云数据实现隐函数拟合。
- The space partition of point cloud was generated using octree structure. k neighborhood was constructed through partition result. 采用八叉树结构对点云数据进行空间分割，由分割结果建立k邻域。
- You can emit particles from multiple scene elements or from a group of objects. When there are multiple objects selected, the same point cloud is emitted from all the objects. 用户可以从多个场景中的元素或者是物体群组发射粒子，当多个物体被选中的时候。从所有的物体上都会发射同样的点云。
