Linked Life Data

21329719

Source:http://linkedlifedata.com/resource/pubmed/id/21329719

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
13
pubmed:dateCreated
2011-7-25
pubmed:abstractText
Visual cognition, high-level vision, mid-level vision and top-down processing all refer to decision-based scene analyses that combine prior knowledge with retinal input to generate representations. The label "visual cognition" is little used at present, but research and experiments on mid- and high-level, inference-based vision have flourished, becoming in the 21st century a significant, if often understated part, of current vision research. How does visual cognition work? What are its moving parts? This paper reviews the origins and architecture of visual cognition and briefly describes some work in the areas of routines, attention, surfaces, objects, and events (motion, causality, and agency). Most vision scientists avoid being too explicit when presenting concepts about visual cognition, having learned that explicit models invite easy criticism. What we see in the literature is ample evidence for visual cognition, but few or only cautious attempts to detail how it might work. This is the great unfinished business of vision research: at some point we will be done with characterizing how the visual system measures the world and we will have to return to the question of how vision constructs models of objects, surfaces, scenes, and events.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1878-5646
pubmed:author
pubmed:copyrightInfo
Copyright © 2011 Elsevier Ltd. All rights reserved.
pubmed:issnType
Electronic
pubmed:day
1
pubmed:volume
51
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1538-51
pubmed:dateRevised
2011-10-31
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Visual cognition.
pubmed:affiliation
Centre Attention & Vision, LPP CNRS UMR 8158, Université Paris Descartes, Paris, France. patrick.cavanagh@parisdescartes.fr
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural