Robust Object Recognition Using Wide Baseline Matching for RoboCup Applications

  • Patricio Loncomilla
  • Javier Ruiz-del-Solar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5001)


As the RoboCup leagues evolve, higher requirements (e.g. object recognition skills) are imposed over the robot vision systems, which cannot be fulfilled using simple mechanisms as pure color segmentation or visual sonar. In this context the main objective of this article is to propose a robust object recognition system, based on the wide-baseline matching between a reference image (object model) and a test image where the object is searched. The wide baseline matching is implemented using local interest points and invariant descriptors. The proposed object recognition system is validated in two real-world tasks, recognition of objects in the RoboCup @Home league, and detection of robots in the humanoid league.


Object Recognition Reference Image Interest Point Humanoid Robot Scale Invariant Feature Transform 
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 2008

Authors and Affiliations

  • Patricio Loncomilla
    • 1
    • 2
  • Javier Ruiz-del-Solar
    • 1
    • 2
  1. 1.Department of Electrical EngineeringUniversidad de Chile 
  2. 2.Center for Web Research, Department of Computer ScienceUniversidad de Chile 

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