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Context-sensitive queries for image retrieval in digital libraries

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Abstract

In this paper we show how to achieve a more effective Query By Example processing, by using active mechanisms of biological vision, such as saccadic eye movements and fixations. In particular, we discuss the way to generate two fixation sequences from a query image I q and a test image I t of the data set, respectively, and how to compare the two sequences in order to compute a similarity measure between the two images. Meanwhile, we show how the approach can be used to discover and represent the hidden semantic associations among images, in terms of categories, which in turn drive the query process.

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Authors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione e Ingegneria Elettrica, via Ponte Melillo 1, 84084, Fisciano (SA), Italy

    G. Boccignone

  2. Dipartimento di Informatica e Sistemistica, via Claudio 21, 80125, Naples, Italy

    A. Chianese, V. Moscato & A. Picariello

Authors
  1. G. Boccignone
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  2. A. Chianese
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  3. V. Moscato
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  4. A. Picariello
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Correspondence to V. Moscato.

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Boccignone, G., Chianese, A., Moscato, V. et al. Context-sensitive queries for image retrieval in digital libraries. J Intell Inf Syst 31, 53–84 (2008). https://doi.org/10.1007/s10844-007-0040-5

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  • DOI: https://doi.org/10.1007/s10844-007-0040-5

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