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Using computational models to study texture representations in the human visual system.

dc.date.accessioned2005-12-22T02:21:13Z
dc.date.accessioned2018-11-24T10:24:23Z
dc.date.available2005-12-22T02:21:13Z
dc.date.available2018-11-24T10:24:23Z
dc.date.issued2005-02-07
dc.identifier.urihttp://hdl.handle.net/1721.1/30521
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/30521
dc.description.abstractTraditionally, human texture perception has been studied using artificial textures made of random-dot patterns or abstract structured elements. At the same time, computer algorithms for the synthesis of natural textures have improved dramatically. The current study seeks to unify these two fields of research through a psychophysical assessment of a particular computational model, thus providing a sense of what image statistics are most vital for representing a range of natural textures. We employ Portilla and Simoncelli s 2000 model of texture synthesis for this task (a parametric model of analysis and synthesis designed to mimic computations carried out by the human visual system). We find an intriguing interaction between texture type (periodic v. structured) and image statistics (autocorrelation function and filter magnitude correlations), suggesting different processing strategies may be employed for these two texture families under pre-attentive viewing.
dc.format.extent11 p.
dc.format.extent33342937 bytes
dc.format.extent4614631 bytes
dc.language.isoen_US
dc.subjectAI
dc.subjecttexture perception
dc.subjecttexture synthesis
dc.subjectpsychophysics
dc.subjectnatural images
dc.titleUsing computational models to study texture representations in the human visual system.


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