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Efficient Multi-resolution Plane Segmentation of 3D Point Clouds

  • Bastian Oehler
  • Joerg Stueckler
  • Jochen Welle
  • Dirk Schulz
  • Sven Behnke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7102)

Abstract

We present an efficient multi-resolution approach to segment a 3D point cloud into planar components. In order to gain efficiency, we process large point clouds iteratively from coarse to fine 3D resolutions: At each resolution, we rapidly extract surface normals to describe surface elements (surfels). We group surfels that cannot be associated with planes from coarser resolutions into co-planar clusters with the Hough transform. We then extract connected components on these clusters and determine a best plane fit through RANSAC. Finally, we merge plane segments and refine the segmentation on the finest resolution. In experiments, we demonstrate the efficiency and quality of our method and compare it to other state-of-the-art approaches.

Keywords

Plane segmentation multi-resolution RANSAC Hough transform 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Bastian Oehler
    • 1
  • Joerg Stueckler
    • 2
  • Jochen Welle
    • 1
  • Dirk Schulz
    • 1
  • Sven Behnke
    • 2
  1. 1.Research Group Unmanned SystemsFraunhofer-Institute for Communication, Information Processing and Ergonomics (FKIE)WachtbergGermany
  2. 2.Computer Science Institute VI, Autonomous Intelligent Systems (AIS)University of BonnBonnGermany

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