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2014
Conference Paper
Titel

Efficient segmentation and surface classification of range images

Abstract
Derivation of geometric structures from point clouds is an important step towards scene understanding for mobile robots. In this paper, we present a novel method for segmentation and surface classification of ordered point clouds. Data from RGB-D cameras are used as input. Normal based region growing segments the cloud and point feature descriptors classify each segment. Not only planar segments can be described but also curved surfaces. In an evaluation on indoor scenes we show the performance of our approach as well as give a comparison to state of the art methods.
Author(s)
Arbeiter, Georg
Fuchs, Steffen
Hampp, Joshua
Bormann, Richard
Hauptwerk
IEEE ICRA 2014, International Conference on Robotics and Automation
Project(s)
ACCOMPANY
Funder
European Commission EC
Konferenz
International Conference on Robotics and Automation (ICRA) 2014
Thumbnail Image
DOI
10.1109/ICRA.2014.6907668
Language
English
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Fraunhofer-Institut fĂĽr Produktionstechnik und Automatisierung IPA
Tags
  • Care-O-bot®

  • mobile robot

  • mobiler Roboter

  • RGB-D

  • service robot

  • Serviceroboter

  • object segmentation

  • Mustererkennung

  • Roboter

  • Oberflächeneigenschaf...

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