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Overview of the CLEF 2009 Robot Vision Track

  • Andrzej Pronobis
  • Li Xing
  • Barbara Caputo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6242)

Abstract

The robot vision track has been proposed to the ImageCLEF participants for the first time in 2009 and attracted considerable attention. The track addressed the problem of visual place recognition applied to robot topological localization. Participants were asked to classify rooms of an office environment on the basis of image sequences captured by a perspective camera mounted on a mobile robot. The algorithms proposed by the participants had to answer the question “where are you?” (I am in the kitchen, in the corridor, etc) when presented with a test sequence imaging rooms seen during training, or additional rooms that were not imaged in the training sequence. The participants were asked to solve the problem separately for each test image (obligatory task). Additionally, results could also be reported for algorithms exploiting the temporal continuity of the image sequences (optional task). Robustness of the algorithms was evaluated in presence of variations introduced by changing illumination conditions and dynamic variations observed across a time span of almost two years. The participants submitted 18 runs to the obligatory task, and 9 to the optional task. The best results were obtained by the Idiap Research Institute, Martigny, Switzerland for the obligatory task and the University of Castilla-La Mancha, Albacete, Spain for the optional task.

Keywords

Support Vector Machine Mobile Robot Little Square Support Vector Machine Training Sequence 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 2010

Authors and Affiliations

  • Andrzej Pronobis
    • 1
  • Li Xing
    • 1
  • Barbara Caputo
    • 2
  1. 1.Centre for Autonomous SystemsThe Royal Institute of TechnologyStockholmSweden
  2. 2.Idiap Research InstituteMartignySwitzerland

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