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The Rules of Guidance in Visual Search

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Perception and Machine Intelligence (PerMIn 2012)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7143))

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Abstract

It is impossible to identify all objects in the visual world at the same time. Accordingly, we must direct attention to specific objects in order to fully recognize them. The deployment of attention is far from random. Attention is guided toward likely targets by a limited set of stimulus attributes such as color and size (“classic guidance”). Attention is also guided by a number of scene-based properties. Thus, if we were looking for sheep, we would expect them on surfaces that could support sheep, not in mid-air. We use information about the 3D layout of a space to determine which objects could plausibly be sheep-sized in that space. This paper briefly reviews the diverse set of guiding properties and the rules that govern their use.

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Author information

Authors and Affiliations

  1. Visual Attention Lab, Brigham and Women’s Hospital & Harvard Medical School, USA

    Jeremy M. Wolfe

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  1. Jeremy M. Wolfe
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Editor information

Editors and Affiliations

  1. Indian Statistical Institute (ISI), Machine Intelligence Unit, Kolkata, India

    Malay K. Kundu  & Sushmita Mitra  & 

  2. Centre for Development of Advanced Computing (C-DAC), Kolkata, India

    Debasis Mazumdar

  3. Indian Statistical Instituten (ISI), Kolkata, India

    Sankar K. Pal

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© 2012 Springer-Verlag Berlin Heidelberg

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Wolfe, J.M. (2012). The Rules of Guidance in Visual Search. In: Kundu, M.K., Mitra, S., Mazumdar, D., Pal, S.K. (eds) Perception and Machine Intelligence. PerMIn 2012. Lecture Notes in Computer Science, vol 7143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27387-2_1

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  • DOI: https://doi.org/10.1007/978-3-642-27387-2_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27386-5

  • Online ISBN: 978-3-642-27387-2

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