SkelTre: Robust skeleton extraction from imperfect point clouds

  • Authors:
  • Alexander Bucksch;Roderik Lindenbergh;Massimo Menenti

  • Affiliations:
  • Delft University of Technology, Kluyverweg 1, 2629 HS, Delft, The Netherlands;Delft University of Technology, Kluyverweg 1, 2629 HS, Delft, The Netherlands;Delft University of Technology, Kluyverweg 1, 2629 HS, Delft, The Netherlands

  • Venue:
  • The Visual Computer: International Journal of Computer Graphics - Special Issue on 3D Object Retrieval 2009
  • Year:
  • 2010

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Abstract

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.