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International Conference on Image and Video Retrieval

CIVR 2003: Image and Video Retrieval pp 291–299Cite as

Towards a Comprehensive Survey of the Semantic Gap in Visual Image Retrieval

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2728))

Abstract

This paper adopts the premise that the’ semantic gap’ is an incompletely surveyed feature in the landscape of visual image retrieval, and proposes a framework within which this deficiency might be made good. Simple classifications of types of image and of types of user are proposed. Consideration is then given in outline to how semantic content is realised by each class of user within each class of image. The argument is advanced that this realisation finds expression in perceptual, generic interpretive and specific interpretive content. This analytic framework provides the basis for the specification of a broadly encompassing evaluation study, which will employ the image/user type classification and the expert domain knowledge of selected user groups in the construction of segmented test collections of real queries, images and relevance judgements. From this study should come a better-informed view on the nature of semantic information need, and on the representation and recovery of semantic content across a broad spectrum of image retrieval activity.

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Author information

Authors and Affiliations

  1. School of Computing, Mathematical and Information Sciences, University of Brighton, UK

    Peter Enser & Christine Sandom

Authors
  1. Peter Enser
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  2. Christine Sandom
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Editor information

Editors and Affiliations

  1. LIACS Media Lab, Leiden University, Niels Bohrweg 1, 2333 CA, Leiden, The Netherlands

    Erwin M. Bakker  & Michael S. Lew  & 

  2. Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 N. Mathews Avenue, Urbana, IL, 61801, USA

    Thomas S. Huang

  3. University of Amsterdam, Kruislaan 403, 1098 SJ, Amsterdam, The Netherlands

    Nicu Sebe

  4. Siemens Corporate Research, 755 College Road East, Princeton, NJ, 08540, USA

    Xiang Sean Zhou

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© 2003 Springer-Verlag Berlin Heidelberg

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Enser, P., Sandom, C. (2003). Towards a Comprehensive Survey of the Semantic Gap in Visual Image Retrieval. In: Bakker, E.M., Lew, M.S., Huang, T.S., Sebe, N., Zhou, X.S. (eds) Image and Video Retrieval. CIVR 2003. Lecture Notes in Computer Science, vol 2728. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45113-7_29

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  • DOI: https://doi.org/10.1007/3-540-45113-7_29

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40634-1

  • Online ISBN: 978-3-540-45113-6

  • eBook Packages: Springer Book Archive

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