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- Designed for combined measurement in photogrammetric images and 3D point clouds from laser scanners, such as the Z390, PHIDIAS software enables the generation of highly accurate and detailed models. 设计合并测量摄影图象和三维点云激光扫描仪;如z390;phidias软件可以生成高度精确和详细模型.
- 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。
- 3D point cloud 三堆点云
- 3D points cloud data 三维海量点云
- 3D point clouds 三维点云
- 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。
- Lastly, lively to reconstruct the surface of relative surface according to images and reconstructed 3D points. 最后,结合精确重建的特征点和图像信息,实现皮肤三维轮廓实时重建。
- 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)。