A Constructive Feature Detection Approach for Robotic Vision

  • Felix von Hundelshausen
  • Michael Schreiber
  • Raúl Rojas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3276)


We describe a new method for detecting features on a marked RoboCup field. We implemented the framework for robots with omnidirectional vision, but the method can be easily adapted to other systems. The focus is on the recognition of the center circle and four different corners occurring in the penalty area. Our constructive approach differs from previous methods, in that we aim to detect a whole palette of different features, hierarchically ordered and possibly containing each other. High-level features, such as the center circle or the corners, are constructed from low-level features such as arcs and lines. The feature detection process starts with low-level features and iteratively constructs higher features. In RoboCup the method is valuable for robot self-localization; in other fields of application the method is useful for object recognition using shape information.


Center Circle Point Sequence Omnidirectional Image Monte Carlo Localization Circle Detection 
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 2005

Authors and Affiliations

  • Felix von Hundelshausen
    • 1
  • Michael Schreiber
    • 1
  • Raúl Rojas
    • 1
  1. 1.Institute of Computer ScienceFree University of BerlinBerlinGermany

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