Properties and limitations of a Foveal visual preprocessor

Emmanuel Marilly; Christophe Coroyer; Alain Faure; Olga Cachard

doi:10.1117/12.380580

30 March 2000 Properties and limitations of a Foveal visual preprocessor

Emmanuel Marilly; Christophe Coroyer; Alain Faure; Olga Cachard

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Proceedings Volume 4055, Applications and Science of Computational Intelligence III; (2000) https://doi.org/10.1117/12.380580
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

We have evolved a Foveal Visual Pre-processor: the Retina model. It is based on an artificial neural network organized to simulate the radial variation of the visual acuity. The information is encoded through the implementation of analogic and impulse neurons. The main interest of this model inspired of this model inspired by the vertebrate retina is its response to stationary or moving stimuli: they can be distinguished according to both their shapes and velocities. This model is adaptive and its multi-resolution characteristics allow the detection of a wide range of velocities. From impulse output signals of Retina, we extract pertinent parameters that encode the motion and pattern information thanks to a time frequency analysis. We study the influence of the different retina areas in the velocity extraction. Our system realizes a very good generalization for classification of stimuli with different level of luminance and noise. The properties of our Retina model: adaptivity, multi-resolution allow us to consider its application on a real time sequence images. A control module combined with this sensor enabled us to reach interesting result in applications such as selective tracking of stimuli, tracking of solid or dotted white line on highway or road, image exploration.

Citation Download Citation

Emmanuel Marilly, Emmanuel Marilly, Christophe Coroyer, Christophe Coroyer, Alain Faure, Alain Faure, Olga Cachard, Olga Cachard, } "Properties and limitations of a Foveal visual preprocessor", Proc. SPIE 4055, Applications and Science of Computational Intelligence III, (30 March 2000); doi: 10.1117/12.380580; https://doi.org/10.1117/12.380580

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