Document Detail


Natural-scene statistics predict how the figure-ground cue of convexity affects human depth perception.
MedLine Citation:
PMID:  20505093     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The shape of the contour separating two regions strongly influences judgments of which region is "figure" and which is "ground." Convexity and other figure-ground cues are generally assumed to indicate only which region is nearer, but nothing about how much the regions are separated in depth. To determine the depth information conveyed by convexity, we examined natural scenes and found that depth steps across surfaces with convex silhouettes are likely to be larger than steps across surfaces with concave silhouettes. In a psychophysical experiment, we found that humans exploit this correlation. For a given binocular disparity, observers perceived more depth when the near surface's silhouette was convex rather than concave. We estimated the depth distributions observers used in making those judgments: they were similar to the natural-scene distributions. Our findings show that convexity should be reclassified as a metric depth cue. They also suggest that the dichotomy between metric and nonmetric depth cues is false and that the depth information provided many cues should be evaluated with respect to natural-scene statistics. Finally, the findings provide an explanation for why figure-ground cues modulate the responses of disparity-sensitive cells in visual cortex.
Authors:
Johannes Burge; Charless C Fowlkes; Martin S Banks
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  The Journal of neuroscience : the official journal of the Society for Neuroscience     Volume:  30     ISSN:  1529-2401     ISO Abbreviation:  J. Neurosci.     Publication Date:  2010 May 
Date Detail:
Created Date:  2010-05-27     Completed Date:  2010-06-15     Revised Date:  2011-07-28    
Medline Journal Info:
Nlm Unique ID:  8102140     Medline TA:  J Neurosci     Country:  United States    
Other Details:
Languages:  eng     Pagination:  7269-80     Citation Subset:  IM    
Affiliation:
School of Optometry, University of California at Berkeley, Berkeley, California 94720-2020, USA. jburge@berkeley.edu
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MeSH Terms
Descriptor/Qualifier:
Analysis of Variance
Cues*
Depth Perception / physiology*
Field Dependence-Independence*
Humans
Models, Biological*
Nature*
Pattern Recognition, Visual / physiology*
Photic Stimulation / methods
Predictive Value of Tests
Probability
Psychophysics
Vision Disparity
Vision, Ocular
Grant Support
ID/Acronym/Agency:
R01 EY014194-03/EY/NEI NIH HHS; R01 EY014194-04/EY/NEI NIH HHS; R01-EY12851/EY/NEI NIH HHS
Comments/Corrections

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