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Building Semantic Hierarchies Faithful to Image Semantics

  • Hichem Bannour
  • Céline Hudelot
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7131)

Abstract

This paper proposes a new image-semantic measure, named ”Semantico-Visual Relatedness of Concepts” (SVRC), to estimate the semantic similarity between concepts. The proposed measure incorporates visual, conceptual and contextual information to provide a measure which is more meaningful and more representative of image semantics. We also propose a new methodology to automatically build a semantic hierarchy suitable for the purpose of image annotation and/or classification. The building is based on the previously proposed measure SVRC and on a new heuristic, named TRUST-ME, to connect concepts with higher relatedness till the building of the final hierarchy. The built hierarchy explicitly encodes a general to specific concepts relationship and therefore provides a semantic structure to concepts which facilitates the semantic interpretation of images. Our experiments showed that the use of the constructed semantic hierarchies as a hierarchical classification framework provides a better image annotation.

Keywords

Visual Word Semantic Similarity Semantic Relatedness Visual Similarity Contextual Similarity 
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 2012

Authors and Affiliations

  • Hichem Bannour
    • 1
  • Céline Hudelot
    • 1
  1. 1.Applied Mathematics and Systems DepartmentEcole Centrale ParisChâtenay-MalabryFrance

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