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Visual Pathways for Detection of Landmark Points

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Artificial Neural Networks – ICANN 2006 (ICANN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4131))

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Abstract

We describe a neuron multi-layered architecture that extracts landmark points of high curvature from 2d shapes and resembles the visual pathway of primates. We demonstrate how the rotated orientation specific receptive fields of the simple neurons that were discovered by Hubel and Wiesel can perform landmark point detection on the 2d contour of the shape that is projected on the retina of the eye. Detection of landmark points of high curvature is a trivial task with sophisticated machine equipment but we demonstrate how such a task can be accomplished by only using the hardware of the visual cortex of primates abiding to the discoveries of Hubel and Wiesel regarding the rotated arrangements of orientation specific simple neurons. The proposed layered architecture first extracts the 2dimensional shape from the projection on the retina then it rotates the extracted shape in multiple layers in order to detect the landmark points. Since rotating the image about the focal origin is equivalent to the rotation of the simple cells orientation field, our model offers an explanation regarding the mystery of the arrangement of the cortical cells in the areas of layer 2 and 3 on the basis of shape cognition from its landmark points.

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Raftopoulos, K., Papadakis, N., Ntalianis, K. (2006). Visual Pathways for Detection of Landmark Points. In: Kollias, S.D., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840817_76

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  • DOI: https://doi.org/10.1007/11840817_76

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38625-4

  • Online ISBN: 978-3-540-38627-8

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