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Overview of the ImageCLEF 2007 Object Retrieval Task

  • Thomas Deselaers
  • Allan Hanbury
  • Ville Viitaniemi
  • András Benczúr
  • Mátyás Brendel
  • Bálint Daróczy
  • Hugo Jair Escalante Balderas
  • Theo Gevers
  • Carlos Arturo Hernández Gracidas
  • Steven C. H. Hoi
  • Jorma Laaksonen
  • Mingjing Li
  • Heidy Marisol Marín Castro
  • Hermann Ney
  • Xiaoguang Rui
  • Nicu Sebe
  • Julian Stöttinger
  • Lei Wu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5152)

Abstract

We describe the object retrieval task of ImageCLEF 2007, give an overview of the methods of the participating groups, and present and discuss the results.

The task was based on the widely used PASCAL object recognition data to train object recognition methods and on the IAPR TC-12 benchmark dataset from which images of objects of the ten different classes bicycles, buses, cars, motorbikes, cats, cows, dogs, horses, sheep, and persons had to be retrieved.

Seven international groups participated using a wide variety of methods. The results of the evaluation show that the task was very challenging and that different methods for relevance assessment can have a strong influence on the results of an evaluation.

Keywords

Image Retrieval Visual Word Interest Point Query Image Image Patch 
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

  • Thomas Deselaers
    • 1
  • Allan Hanbury
    • 2
  • Ville Viitaniemi
    • 3
  • András Benczúr
    • 4
  • Mátyás Brendel
    • 4
  • Bálint Daróczy
    • 4
  • Hugo Jair Escalante Balderas
    • 5
  • Theo Gevers
    • 6
  • Carlos Arturo Hernández Gracidas
    • 5
  • Steven C. H. Hoi
    • 7
  • Jorma Laaksonen
    • 3
  • Mingjing Li
    • 8
  • Heidy Marisol Marín Castro
    • 5
  • Hermann Ney
    • 1
  • Xiaoguang Rui
    • 8
  • Nicu Sebe
    • 6
  • Julian Stöttinger
    • 2
  • Lei Wu
    • 8
  1. 1.Computer Science DepartmentRWTH Aachen UniversityGermany
  2. 2.Pattern Recognition and Image Processing Group (PRIP), Institute of Computer-Aided AutomationVienna University of TechnologyAustria
  3. 3.Adaptive Informatics Research CentreHelsinki University of TechnologyFinland
  4. 4.Data Mining and Web search Research GroupComputer and Automation Research Institute of the Hungarian Academy of SciencesBudapestHungary
  5. 5.TIA Research Group, Computer Science DepartmentNational Institute of Astrophysics, Optics and ElectronicsTonantzintlaMexico
  6. 6.Intelligent Systems Lab AmsterdamUniversity of AmsterdamThe Netherlands
  7. 7.School of Computer EngineeringNanyang Technological UniversitySingapore
  8. 8.Microsoft Research AsiaBeijingChina

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