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A Proto-object Based Visual Attention Model

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Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint (WAPCV 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4840))

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Abstract

One of the first steps of any visual system is that of locating suitable interest points, ‘salient regions’, in the scene, to detect events, and eventually to direct gaze toward these locations. In the last few years, object-based visual attention models have received an increasing interest in computational neuroscience and in computer vision, the problem, in this case, being that of creating a model of ‘objecthood’ that eventually guides a saliency mechanism. We present here an model of visual attention based on the definition of ‘proto-objects’ and show its instantiation on a humanoid robot. Moreover we propose a biological plausible way to learn certain Gestalt rules that can lead to proto-objects.

This work was supported by EU project RobotCub (IST- 2004-004370) and CONTACT (NEST-5010).

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Author information

Authors and Affiliations

  1. DIST, University of Genoa, Viale Causa, 13 - Genoa 16145, Italy

    Francesco Orabona & Giorgio Metta

  2. Italian Institute of Technology, Via Morego, 30 - Genoa 16163, Italy

    Giorgio Metta & Giulio Sandini

Authors
  1. Francesco Orabona
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  2. Giorgio Metta
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  3. Giulio Sandini
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Editors and Affiliations

  1. Joanneum Research, Forschungsgesellschaft mbH, Computational Perception Group,, Institute of Digital Image Processing, Wastiangasse 6, 8010, Graz, Austria

    Lucas Paletta

  2. Autonomous Intelligent Systems (AIS), Autonomous Robots Department, Fraunhofer Institute, Schloss Birlinghoven, 53754, Sankt Augustin, Germany

    Erich Rome

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© 2007 Springer-Verlag Berlin Heidelberg

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Orabona, F., Metta, G., Sandini, G. (2007). A Proto-object Based Visual Attention Model. In: Paletta, L., Rome, E. (eds) Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint. WAPCV 2007. Lecture Notes in Computer Science(), vol 4840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77343-6_13

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  • DOI: https://doi.org/10.1007/978-3-540-77343-6_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77342-9

  • Online ISBN: 978-3-540-77343-6

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