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Bio-inspired Connectionist Architecture for Visual Detection and Refinement of Shapes

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Artificial Neural Networks – ICANN 2009 (ICANN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5769))

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Abstract

In this paper we propose a bio-inspired architecture for the visual reconstruction of silhouettes of moving objects, based on the behaviour of simple cells, complex cells and the Long-Range interactions of these neurons present in the primary visual cortex of the primates. This architecture was tested with real sequences of images acquired in natural environments. The results combined with our previous results show the flexibility of our propose since it allows not only to reconstruct the silhouettes of objects in general, but also, allows to distinguish between different types of objects in motion. This distinction is necessary since our future objective is the identification of people by their gait.

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Author information

Authors and Affiliations

  1. Laboratory of Information Technology of Centre for Research and Advanced Studies, LTI Cinvestav - Tamaulipas, Ciudad Victoria, Tamaulipas, México

    Pedro L. Sánchez Orellana & Claudio Castellanos Sánchez

Authors
  1. Pedro L. Sánchez Orellana
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  2. Claudio Castellanos Sánchez
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Editor information

Editors and Affiliations

  1. Dipartimento di Elettronica, Politecnico di Milano, Piazza L. da Vinci 32, 20133, Milano, Italy

    Cesare Alippi

  2. Department of Electrical and Computer Engineering, University of Cyprus, 75 Kallipoleos Street, 1678, Nicosia, Cyprus

    Marios Polycarpou , Christos Panayiotou  & Georgios Ellinas ,  & 

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© 2009 Springer-Verlag Berlin Heidelberg

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Sánchez Orellana, P.L., Castellanos Sánchez, C. (2009). Bio-inspired Connectionist Architecture for Visual Detection and Refinement of Shapes. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds) Artificial Neural Networks – ICANN 2009. ICANN 2009. Lecture Notes in Computer Science, vol 5769. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04277-5_75

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  • DOI: https://doi.org/10.1007/978-3-642-04277-5_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04276-8

  • Online ISBN: 978-3-642-04277-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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