A neural model with feedback for robust disambiguation of motion

Mauricio Cerda 1 Bernard Girau 1
1 CORTEX - Neuromimetic intelligence
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : The aperture problem is a direct consequence of any local detection in the visual perception of motion. It results in ambiguous responses of the local motion detectors. Biological systems, such as the brain of different mammals, are able to disambiguate motion detection. Such disambiguation is usually seen as a possible result of a pyramidal feedforward processing with growing receptive fields, but this approach is not able to detect motion in a simultaneously unambiguous and precise way. In this work we define a neural model of motion disambiguation that achieves both criteria, mainly with the help of excitatory feedback. Our model mostly differs from previous ones by incorporating lateral inhibition. Its main advantages are: tolerance to noise and stability. We perform tests on synthetic image sequences that show the effectiveness of our approach.
Type de document :
Communication dans un congrès
ESANN 2008, 16th European Symposium on Artificial Neural Networks, Bruges, Belgium, April 23-25, 2008, Proceedings, Apr 2008, Bruges, Belgium. pp.505-510, 2008
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https://hal.inria.fr/inria-00331645
Contributeur : Mauricio Cerda <>
Soumis le : vendredi 17 octobre 2008 - 11:20:19
Dernière modification le : jeudi 11 janvier 2018 - 06:19:48

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  • HAL Id : inria-00331645, version 1

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Mauricio Cerda, Bernard Girau. A neural model with feedback for robust disambiguation of motion. ESANN 2008, 16th European Symposium on Artificial Neural Networks, Bruges, Belgium, April 23-25, 2008, Proceedings, Apr 2008, Bruges, Belgium. pp.505-510, 2008. 〈inria-00331645〉

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