A kernel-based framework for image collection exploration

  • Authors:
  • Jorge E. Camargo;Juan C. Caicedo;Fabio A. Gonzalez

  • Affiliations:
  • Departamento de Ingeniería de Sistemas e Industrial, Universidad Nacional de Colombia, Bogotá Of. 114 Edif. 453 (Aulas de Ingeniería), Colombia;Departamento de Ingeniería de Sistemas e Industrial, Universidad Nacional de Colombia, Bogotá Of. 114 Edif. 453 (Aulas de Ingeniería), Colombia;Departamento de Ingeniería de Sistemas e Industrial, Universidad Nacional de Colombia, Bogotá Of. 114 Edif. 453 (Aulas de Ingeniería), Colombia

  • Venue:
  • Journal of Visual Languages and Computing
  • Year:
  • 2013

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Abstract

While search engines have been a successful tool to search text information, image search systems still face challenges. The keyword-based query paradigm used to search in image collection systems, which has been successful in text retrieval, may not be useful in scenarios where the user does not have the precise way to express a visual query. Image collection exploration is a new paradigm where users interact with the image collection to discover useful and relevant pictures. This paper proposes a framework for the construction of an image collection exploration system based on kernel methods, which offers a mathematically strong basis to address each stage of an image collection exploration system: image representation, summarization, visualization and interaction. In particular, our approach emphasizes a semantic representation of images using kernel functions, which can be seamlessly harnessed across all system components. Experiments were conducted with real users to verify the effectiveness and efficiency of the proposed strategy.