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An Efficient Encoding Scheme for Dynamic Visual Input Based on the Statistics of Natural Optic Flow

  • Dirk Calow
  • Markus Lappe
Conference paper

Abstract

Statistically efficient processing schemes focus the resources of a signal processing system on the range of statistically probable signals. Relying on the statistical properties of retinal motion signals during ego-motion we propose a nonlinear processing scheme for retinal flow. It maximizes the mutual information between the visual input and its neural representation and distributes the processing load uniformly over the neural resources. We derive predictions for the receptive fields of motion sensitive neurons in the velocity space. The properties of the receptive fields are tightly connected to their position in the visual field and to their preferred retinal velocity. The velocity tuning properties show characteristics of properties of neurons in the middle temporal area of the primate brain.

Keywords

Encode Scheme Transformation Function Independent Component Analysis Motion Signal Range Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Dirk Calow
    • 1
  • Markus Lappe
  1. 1.Department of PsychologyWestf.- Wilhelms University48149 MünsterGermany

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