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Relative Influence of Bottom-Up and Top-Down Attention

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Book cover Attention in Cognitive Systems (WAPCV 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5395))

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Abstract

Attention and memory are very closely related and their aim is to simplify the acquired data into an intelligent structured data set. Two main points are discussed in this paper. The first one is the presentation of a novel visual attention model for still images which includes both a bottom-up and a top-down approach. The bottom-up model is based on structures rarity within the image during the forgetting process. The top-down information uses mouse-tracking experiments to build models of a global behavior for a given kind of image. The proposed models assessment is achieved on a 91-image database. The second interesting point is that the relative importance of bottom-up and top-down attention depends on the specificity of each image. In unknown images the bottom-up influence remains very important while in specific kinds of images (like web sites) top-down attention brings the major information.

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Author information

Authors and Affiliations

  1. Engineering Faculty of Mons (FPMs), 31, Bd. Dolez, 7000, Mons, Belgium

    Matei Mancas

Authors
  1. Matei Mancas
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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., ON M3J 1P3, Toronto, Canada

    John K. Tsotsos

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© 2009 Springer-Verlag Berlin Heidelberg

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Mancas, M. (2009). Relative Influence of Bottom-Up and Top-Down Attention. In: Paletta, L., Tsotsos, J.K. (eds) Attention in Cognitive Systems. WAPCV 2008. Lecture Notes in Computer Science(), vol 5395. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00582-4_16

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  • DOI: https://doi.org/10.1007/978-3-642-00582-4_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00581-7

  • Online ISBN: 978-3-642-00582-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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