From Mathematical Image Analysis to Neurogeometry of the Brain

LADISLAV TAUC CONFERENCES & GDR MSPC NEUROSCIENCE Joint Meeting

• http://www.conftauc.cnrs-gif.fr/programme.php

• watch the presentation (150 Mo with movies)

• see the accompanying poster

• see this more recent talk

• see more :

  • on MotionPerception

  • on MotionParticles

reference

• Laurent Perrinet. Probabilistic models of the low-level visual system: the role of prediction in detecting motion, URL . In LADISLAV TAUC & GDR MSPC NEUROSCIENCES CONFERENCE, From Mathematical Image Analysis to Neurogeometry of the Brain, 2010 abstract
  Sensory informations such as visual images are inherently variable. We use probabilistic models to describe how the low-level visual system could describe superposed and ambiguous information. This allows to describe the interactions of neighboring populations of neurons as inference rules that dynamically build up the overall description of the visual scene. We focus here on temporal prediction, that is by the transport of information based on an estimate of local motion in the image.
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