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Covert Attention with a Spiking Neural Network

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Computer Vision Systems (ICVS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5008))

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Abstract

We propose an implementation of covert attention mechanisms with spiking neurons. Spiking neural models describe the activity of a neuron with precise spike-timing rather than firing rate. We investigate the interests offered by such a temporal code for low-level vision and early attentional process. This paper describes a spiking neural network which achieves saliency extraction and stable attentional focus of a moving stimulus. Experimental results obtained using real visual scene illustrate the robustness and the quickness of this approach.

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Author information

Authors and Affiliations

  1. Université Paris-Sud XI, France

    Sylvain Chevallier

  2. LIMSI-CNRS UPR 3251, Orsay, France

    Sylvain Chevallier & Philippe Tarroux

  3. École Normale Supérieure, Paris, France

    Philippe Tarroux

Authors
  1. Sylvain Chevallier
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  2. Philippe Tarroux
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Editor information

Antonios Gasteratos Markus Vincze John K. Tsotsos

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© 2008 Springer-Verlag Berlin Heidelberg

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Chevallier, S., Tarroux, P. (2008). Covert Attention with a Spiking Neural Network. In: Gasteratos, A., Vincze, M., Tsotsos, J.K. (eds) Computer Vision Systems. ICVS 2008. Lecture Notes in Computer Science, vol 5008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79547-6_6

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  • DOI: https://doi.org/10.1007/978-3-540-79547-6_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79546-9

  • Online ISBN: 978-3-540-79547-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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