A Clustered Retrieval Approach for Categorizing and Annotating Images

  • Lisa Ballesteros
  • Desislava Petkova
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4022)


Images are difficult to classify and annotate but the availability of digital image databases creates a constant demand for tools that automatically analyze image content and describe it with either a category or set of words. We develop two cluster-based cross-media relevance models that effectively categorize and annotate images by adapting a cross-lingual retrieval technique to choose the terms most likely associated with the visual features of an image.


Language Model Visual Feature Training Image Automatic Image Annotation Annotate Image 
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 2006

Authors and Affiliations

  • Lisa Ballesteros
    • 1
  • Desislava Petkova
    • 1
  1. 1.Mount Holyoke CollegeSouth HadleyUSA

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