Predictions for Visual Coding and Performance from the Statistical Properties of Natural Scenes

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Air date:	Monday, September 27, 2010, 12:00:00 PM Time displayed is Eastern Time, Washington DC Local
Views:	Total views: 139 * This only includes stats from October 2011 and forward.
Category:	Neuroscience
Runtime:	01:08:52
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Description:	Research in Dr. Geisler's lab is directed at a wide range of topics in human, monkey and machine vision. Many of the current and recent studies are cast within the framework of “natural systems analysis,” which consists of several components: (i) identify specific natural tasks, (ii) measure the natural scene statistics relevant to performing the tasks, (iii) determine how to optimally use the natural scene statistics to perform the tasks, and (iv) use the first three components to formulate principled hypotheses and test them in behavioral or neurophysiological experiments. Topics currently of particular interest include perceptual grouping, visual search with eye movements, encoding and decoding of neural population responses in retina and visual cortex, defocus estimation, and target detection in the visual periphery. The research is supported primarily with grants from the National Eye Institute. NIH Neuroscience Seminar Series

NLM Title:	Predictions for visual coding and performance from the statistical properties of natural scenes / Wilson S. Geisler.
Author:	Geisler, Wilson S. National Institutes of Health (U.S.)
Publisher:
Subjects:	Photic Stimulation--methods Reaction Time--physiology Visual Cortex--physiology Visual Perception--physiology
Publication Types:	Lecture Webcast
NLM Classification:	WW 105
NLM ID:	101549177
CIT Live ID:	9481
Permanent link:	https://videocast.nih.gov/watch=9481

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