A Multi-class Kernel Alignment Method for Image Collection Summarization

  • Jorge E. Camargo
  • Fabio A. González
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)


This paper proposes a method for involving domain knowledge in the construction of summaries of large collections of images. This is accomplished by using a multi-class kernel alignment strategy in order to learn a kernel function that incorporates domain knowledge (class labels). The kernel function is the basis of a clustering algorithm that generates a subset, the summary, of the image collection. The method was tested with a subset of the Corel image collection using a summarization quality measure based on information theory. Experimental results show that it is possible to improve the quality of the summary when domain knowledge is involved.


Image collection summarization information visualization clustering multi-class kernel alignment 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Jorge E. Camargo
    • 1
  • Fabio A. González
    • 1
  1. 1.Bioingenium Research GroupNational University of Colombia 

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