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Hierarchical Combination of Semantic Visual Words for Image Classification and Clustering

  • Vinicius von Glehn De Filippo
  • Zenilton Kleber G. do PatrocínioJr.Email author
  • Silvio Jamil F. Guimarães
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9423)

Abstract

Image classification and image clustering are two important tasks related to image analysis. In this work a two-level hierarchical model for both tasks using a hierarchical combination of image descriptors is presented. The construction of a latent semantic representation for images is also presented and its impact on the results of both tasks for the two-level hierarchical model is evaluated. Experiments have shown the superior performance attained by the hierarchical combination of descriptors when compared to the simple concatenation of them or to the use of single descriptors. The hierarchical combination of a latent semantic representation has presented results similar to the other hierarchical combinations, using only a small fraction of the time and space needed by others, which is interesting specially for those with restrictions of computer power and/or storage space.

Keywords

Hierarchical combination of descriptors Image classification Image clustering Semantic visual vocabulary 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Vinicius von Glehn De Filippo
    • 1
  • Zenilton Kleber G. do PatrocínioJr.
    • 2
    Email author
  • Silvio Jamil F. Guimarães
    • 2
  1. 1.Instituto PolitécnicoCentro Universitário UNABelo HorizonteBrazil
  2. 2.Pontifícia Universidade Católica de Minas GeraisBelo HorizonteBrazil

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