Efficient multi-resolution plane segmentation of 3d point clouds

Authors:
Bastian Oehler;Joerg Stueckler;Jochen Welle;Dirk Schulz;Sven Behnke
Affiliations:
Research Group Unmanned Systems, Fraunhofer-Institute for Communication, Information Processing and Ergonomics (FKIE), Wachtberg, Germany;Computer Science Institute VI, Autonomous Intelligent Systems (AIS), University of Bonn, Bonn, Germany;Research Group Unmanned Systems, Fraunhofer-Institute for Communication, Information Processing and Ergonomics (FKIE), Wachtberg, Germany;Research Group Unmanned Systems, Fraunhofer-Institute for Communication, Information Processing and Ergonomics (FKIE), Wachtberg, Germany;Computer Science Institute VI, Autonomous Intelligent Systems (AIS), University of Bonn, Bonn, Germany
Venue:
ICIRA'11 Proceedings of the 4th international conference on Intelligent Robotics and Applications - Volume Part II
Year:
2011

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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.