Neighbor detection in point clouds using the Boundary Complex

Simon Brenner
Neighbor detection in point clouds using the Boundary Complex
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Abstract

For many applications (e.g. robotic vision) it is important to separate the Point Clouds produced by a 3D scanner into logically associated clusters in order to recognize objects or surfaces. A crucial part of most of the existing segmentation approaches is the definition of neighborhood between points. This thesis describes and evaluates the use of the ‘Boundary Complex’, a spanning connected set of triangles on the point cloud, for neighbor detection in the context of cloud segmentation. The results will be compared to existing neighbor picking approaches.

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@bachelorsthesis{brenner_simon-2013-ba,
  title =      "Neighbor detection in point clouds using the Boundary
               Complex",
  author =     "Simon Brenner",
  year =       "2013",
  abstract =   "For many applications (e.g. robotic vision) it is important
               to separate the Point Clouds produced by a 3D scanner into
               logically associated clusters in order to recognize objects
               or surfaces. A crucial part of most of the existing
               segmentation approaches is the definition of neighborhood
               between points. This thesis describes and evaluates the use
               of the ‘Boundary Complex’, a spanning connected set of
               triangles on the point cloud, for neighbor detection in the
               context of cloud segmentation. The results will be compared
               to existing neighbor picking approaches.",
  address =    "Favoritenstrasse 9-11/186, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology",
  keywords =   "segmentation, neighbor detection, clustering, boundary
               complex, point cloud",
  URL =        "http://www.cg.tuwien.ac.at/research/publications/2013/brenner_simon-2013-ba/",
}