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Combining Conspicuity Maps for hROIs Prediction

  • Conference paper
Attention and Performance in Computational Vision (WAPCV 2004)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3368))

  • 598 Accesses

Abstract

Bottom-up cortical representations of visual conspicuity interact with top-down internal cognitive models of the external world to control eye movements, EMs, and the closely linked attention-shift mechanisms; to thus achieve visual recognition. Conspicuity operators implemented with image processing algorithms, IPAs, can discriminate human Regions-of-Interest, hROIs, the loci of eye fixations, from the rest of the visual stimulus that is not visited during the EM process. This discrimination generates predictability of the hROIs. Further, a combination of IPA-generated conspicuity maps can be used to achieve improved performance over each of the individual composing maps in terms of hROI predictions.

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Author information

Authors and Affiliations

  1. Neurology and Telerobotics Units, Optometry School, University of California, Berkeley, 94720, CA

    Claudio M. Privitera, Toyomi Fujita & Lawrence W. Stark

  2. Department of Bioengineering of Politecnico di Milano, P.zza Leonardo da Vinci, 20133, Milan

    Orazio Gallo & Giorgio Grimoldi

Authors
  1. Claudio M. Privitera
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  2. Orazio Gallo
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  3. Giorgio Grimoldi
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  4. Toyomi Fujita
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  5. Lawrence W. Stark
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Editor information

Editors and Affiliations

  1. Joanneum Research, Graz, Austria

    Lucas Paletta

  2. Center for Vision Research (CVR) and, Department of Computer Science and Engineering, York University, 4700 Keele St., M3J 1P3, Toronto, ON, Canada

    John K. Tsotsos

  3. Fraunhofer IAIS, Sankt Augustin, Germany

    Erich Rome

  4. Behavioural Brain Sciences Centre, School of Psychology, University of Birmingham, B15 2TT, Edgbaston, UK

    Glyn Humphreys

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© 2005 Springer-Verlag Berlin Heidelberg

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Privitera, C.M., Gallo, O., Grimoldi, G., Fujita, T., Stark, L.W. (2005). Combining Conspicuity Maps for hROIs Prediction. In: Paletta, L., Tsotsos, J.K., Rome, E., Humphreys, G. (eds) Attention and Performance in Computational Vision. WAPCV 2004. Lecture Notes in Computer Science, vol 3368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30572-9_6

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  • DOI: https://doi.org/10.1007/978-3-540-30572-9_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24421-9

  • Online ISBN: 978-3-540-30572-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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