Real-Time Plane Segmentation Using RGB-D Cameras

  • Dirk Holz
  • Stefan Holzer
  • Radu Bogdan Rusu
  • Sven Behnke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7416)

Abstract

Real-time 3D perception of the surrounding environment is a crucial precondition for the reliable and safe application of mobile service robots in domestic environments. Using a RGB-D camera, we present a system for acquiring and processing 3D (semantic) information at frame rates of up to 30Hz that allows a mobile robot to reliably detect obstacles and segment graspable objects and supporting surfaces as well as the overall scene geometry. Using integral images, we compute local surface normals. The points are then clustered, segmented, and classified in both normal space and spherical coordinates. The system is tested in different setups in a real household environment.

The results show that the system is capable of reliably detecting obstacles at high frame rates, even in case of obstacles that move fast or do not considerably stick out of the ground. The segmentation of all planes in the 3D data even allows for correcting characteristic measurement errors and for reconstructing the original scene geometry in far ranges.

Keywords

Point Cloud Collision Avoidance Latent Dirichlet Allocation Integral Image Distance Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dirk Holz
    • 1
  • Stefan Holzer
    • 2
  • Radu Bogdan Rusu
    • 3
  • Sven Behnke
    • 1
  1. 1.Autonomous Intelligent Systems GroupUniversity of BonnGermany
  2. 2.Department of Computer ScienceTechnical University of Munich (TUM)Germany
  3. 3.Willow Garage, Inc.Menlo ParkUSA

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