%0 Conference Paper %1 Perrinet10 %A Perrinet, Laurent %B LADISLAV TAUC & GDR MSPC NEUROSCIENCES CONFERENCE, From Mathematical Image Analysis to Neurogeometry of the Brain %D 2010 %K 2d\_motion bayesian\_modeling center-surround divisive\_normalization motion\_perception motion\_segmentation navier-stokes neural\_masses neuronal\_representation ocular\_following\_response particle\_filter pde probabilistic\_framework %T Probabilistic models of the low-level visual system: the role of prediction in detecting motion %U http://www.incm.cnrs-mrs.fr/LaurentPerrinet/Presentations/10-12-17\_TaucTalk %X 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.

@inproceedings{Perrinet10, 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.}}, added-at = {2011-05-09T11:38:10.000+0200}, author = {Perrinet, Laurent}, biburl = {https://www.bibsonomy.org/bibtex/27cdeb6a62d5cbb845248066b7a7da6c4/meduz}, booktitle = {LADISLAV TAUC \& GDR MSPC NEUROSCIENCES CONFERENCE, From Mathematical Image Analysis to Neurogeometry of the Brain}, citeulike-article-id = {8459692}, citeulike-linkout-0 = {http://www.incm.cnrs-mrs.fr/LaurentPerrinet/Presentations/10-12-17\_TaucTalk}, groups = {public}, interhash = {b70112eab2f1ce2de98260adb3f166bf}, intrahash = {7cdeb6a62d5cbb845248066b7a7da6c4}, keywords = {2d\_motion bayesian\_modeling center-surround divisive\_normalization motion\_perception motion\_segmentation navier-stokes neural\_masses neuronal\_representation ocular\_following\_response particle\_filter pde probabilistic\_framework}, posted-at = {2010-12-20 10:55:39}, priority = {0}, timestamp = {2011-05-09T15:46:19.000+0200}, title = {{Probabilistic models of the low-level visual system: the role of prediction in detecting motion}}, url = {http://www.incm.cnrs-mrs.fr/LaurentPerrinet/Presentations/10-12-17\_TaucTalk}, username = {meduz}, year = 2010 }