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A Geometric Model for the Functional Circuits of the Visual Front-End

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Brain-Inspired Computing (BrainComp 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8603))

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Abstract

This paper reviews a biologically-inspired geometric model for the functional circuits of the visual front-end. An axiomatic approach is taken towards the filters and their tasks in early vision. A high-dimensional Lie-group based approach models the convolutions of the receptive fields in a multi-scale, multi-orientation, multi-velocity, multi-spatial frequency, multi-disparity and multi-color framework. In these new, and essentially invertible, extra-dimensional expansions new geometric reasoning can be developed. They give a feasible approach to the understanding of context, Gestalt, and association fields and enable full exploitation of adaptive, geometry-driven strategies, such as for contour completion and convection. The high-dimensionality leads to high computational costs, but, just as in human vision, this can be solved by massively parallel implementations, which is one of the goals of the EU Human brain project.

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Notes

  1. 1.

    See for most Mathematica code of the formulas in this chapter the book: [16].

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Authors and Affiliations

  1. Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands

    Bart M. ter Haar Romeny

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  1. Bart M. ter Haar Romeny
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Correspondence to Bart M. ter Haar Romeny .

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Editors and Affiliations

  1. Faculty of Engineering, University of Calabria, Arcavacada di Rende, Italy

    Lucio Grandinetti

  2. Jülich Supercomputing Centre, Jülich, Germany

    Thomas Lippert

  3. Computing Science, University of Groningen Institute for Mathematics &, Groningen, The Netherlands

    Nicolai Petkov

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ter Haar Romeny, B.M. (2014). A Geometric Model for the Functional Circuits of the Visual Front-End. In: Grandinetti, L., Lippert, T., Petkov, N. (eds) Brain-Inspired Computing. BrainComp 2013. Lecture Notes in Computer Science(), vol 8603. Springer, Cham. https://doi.org/10.1007/978-3-319-12084-3_4

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  • DOI: https://doi.org/10.1007/978-3-319-12084-3_4

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  • Online ISBN: 978-3-319-12084-3

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