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Using Relevance Feedback to Bridge the Semantic Gap

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Adaptive Multimedia Retrieval: User, Context, and Feedback (AMR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3877))

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Abstract

In this article relevant developments in relevance feedback based image annotation and retrieval are reported. A new approach to infer semantic concepts representing meaningful objects in images is also described. The proposed technique combines user relevance feedback and underlying low-level properties of elementary building blocks making up semantic objects in images. Images are regarded as mosaics made of small building blocks featuring good representations of colour, texture and edgeness. The approach is based on accurate classification of these building blocks. Once this has been achieved, a signature for the object of concern is built. It is expected that this signature features a high discrimination power and consequently it becomes very suitable to find other images containing the same semantic object. The model combines fuzzy clustering and relevance feedback in the training stage, and uses fuzzy support vector machines in the generalization stage.

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Author information

Authors and Affiliations

  1. Queen Mary University of London, MileEnd Road, E1 4NS, London, UK

    Ebroul Izquierdo & Divna Djordjevic

Authors
  1. Ebroul Izquierdo
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  2. Divna Djordjevic
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Editor information

Editors and Affiliations

  1. Laboratoire d’Informatique de Paris 6, France

    Marcin Detyniecki

  2. Department of Computer Science, University of Glasgow, 17 Lilybank Gardens, G12 8QQ, Glasgow, UK

    Joemon M. Jose

  3. Fakultät für Informatik, Otto-von-Guericke Universität Madgeburg, Universitätsplatz 2, 39106, Germany

    Andreas Nürnberger

  4. Department of Computing Science, University of Glasgow, G12 8QQ, Glasgow, UK

    C. J. van Rijsbergen

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© 2006 Springer-Verlag Berlin Heidelberg

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Izquierdo, E., Djordjevic, D. (2006). Using Relevance Feedback to Bridge the Semantic Gap. In: Detyniecki, M., Jose, J.M., Nürnberger, A., van Rijsbergen, C.J. (eds) Adaptive Multimedia Retrieval: User, Context, and Feedback. AMR 2005. Lecture Notes in Computer Science, vol 3877. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11670834_2

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  • DOI: https://doi.org/10.1007/11670834_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-32174-3

  • Online ISBN: 978-3-540-32175-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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