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ESANN
2008

A neural model with feedback for robust disambiguation of motion

10 years 1 days ago
A neural model with feedback for robust disambiguation of motion
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.
Mauricio Cerda, Bernard Girau
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where ESANN
Authors Mauricio Cerda, Bernard Girau
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