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Object Detection and Classification for Domestic Robots

  • Markus Vincze
  • Walter Wohlkinger
  • Sven Olufs
  • Peter Einramhof
  • Robert Schwarz
  • Karthik Varadarajan
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 336)

Abstract

A main task for domestic robots is to navigate safely at home, find places and detect objects. We set out to exploit the knowledge available to the robot to constrain the task of understanding the structure of its environment, i.e., ground for safe motion and walls for localisation, to simplify object detection and classification. We start from exploiting the known geometry and kinematics of the robot to obtain ground point disparities. This considerably improves robustness in combination with a histogram approach over patches in the disparity image. We then show that stereo data can be used for localisation and eventually for object detection classification and that this system approach improves object detection and classification rates considerably.

Keywords

Mobile Robot Ground Plane Object Class Support Plane Stereo Camera 
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

  • Markus Vincze
    • 1
  • Walter Wohlkinger
    • 1
  • Sven Olufs
    • 1
  • Peter Einramhof
    • 1
  • Robert Schwarz
    • 1
  • Karthik Varadarajan
    • 1
  1. 1.Technische Universität WienViennaAustria

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