SkelTre Robust skeleton extraction from imperfect point clouds
SkelTre Robust skeleton extraction from imperfect point clouds
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DOI：
10.1007/s00371-010-0520-4
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发表时间：
2010-10-01
期刊：
影响因子：
3.5
通讯作者：
Menenti, Massimo
中科院分区：
文献类型：
--
作者：
Bucksch, Alexander;Lindenbergh, Roderik;Menenti, Massimo
地面激光扫描仪将真实的世界物体的3D几何形状捕获为点云。本文提出了一种新的激光扫描点云数据的离散化算法。本文提出的点云化算法包括三个步骤：（i）从八叉树组织中提取图，（ii）将图简化为骨架，以及（iii）将骨架嵌入点云。对于这三个步骤，只需要一个输入参数。激光扫描仪点云代表2类对象的结果进行了验证，首先在植物树作为一个特殊的应用程序，其次在流行的任意对象。所提出的骨架发现它的第一个应用程序在获得植物树的参数，如长度和直径的分支，并在这里提出了一个新的，广义的版本。其定义为Reeb图，证明了骨架对于形状分析等应用的有用性。在本文中，我们证明了生成的骨架包含Reeb图，并研究了实际相关的参数：中心性和拓扑正确性。在真实的数据实例上证明了该方法对欠采样、点密度变化和点云系统误差的鲁棒性。
Terrestrial laser scanners capture 3D geometry of real world objects as a point cloud. This paper reports on a new algorithm developed for the skeletonization of a laser scanner point cloud. The skeletonization algorithm proposed in this paper consists of three steps: (i) extraction of a graph from an octree organization, (ii) reduction of the graph to a skeleton, and (iii) embedding of the skeleton into the point cloud. For these three steps, only one input parameter is required. The results are validated on laser scanner point clouds representing 2 classes of objects; first on botanic trees as a special application and secondly on popular arbitrary objects. The presented skeleton found its first application in obtaining botanic tree parameters like length and diameter of branches and is presented here in a new, generalized version. Its definition as Reeb Graph, proofs the usefulness of the skeleton for applications like shape analysis. In this paper we show that the resulting skeleton contains the Reeb Graph and investigate the practically relevant parameters: centeredness and topological correctness. The robustness of this skeletonization method against undersampling, varying point density and systematic errors of the point cloud is demonstrated on real data examples.