Document Detail


The utility of shape attributes in deciphering movements of non-rigid objects.
MedLine Citation:
PMID:  20884524     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Most moving objects in the world are non-rigid, changing shape as they move. To disentangle shape changes from movements, computational models either fit shapes to combinations of basis shapes or motion trajectories to combinations of oscillations but are biologically unfeasible in their input requirements. Recent neural models parse shapes into stored examples, which are unlikely to exist for general shapes. We propose that extracting shape attributes, e.g., symmetry, facilitates veridical perception of non-rigid motion. In a new method, identical dots were moved in and out along invisible spokes, to simulate the rotation of dynamically and randomly distorting shapes. Discrimination of rotation direction measured as a function of non-rigidity was 90% as efficient as the optimal Bayesian rotation decoder and ruled out models based on combining the strongest local motions. Remarkably, for non-rigid symmetric shapes, observers outperformed the Bayesian model when perceived rotation could correspond only to rotation of global symmetry, i.e., when tracking of shape contours or local features was uninformative. That extracted symmetry can drive perceived motion suggests that shape attributes may provide links across the dorsal-ventral separation between motion and shape processing. Consequently, the perception of non-rigid object motion could be based on representations that highlight global shape attributes.
Authors:
Elias H Cohen; Anshul Jain; Qasim Zaidi
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Publication Detail:
Type:  Comparative Study; Journal Article; Research Support, N.I.H., Extramural     Date:  2010-09-30
Journal Detail:
Title:  Journal of vision     Volume:  10     ISSN:  1534-7362     ISO Abbreviation:  J Vis     Publication Date:  2010  
Date Detail:
Created Date:  2010-10-04     Completed Date:  2011-03-17     Revised Date:  2014-09-15    
Medline Journal Info:
Nlm Unique ID:  101147197     Medline TA:  J Vis     Country:  United States    
Other Details:
Languages:  eng     Pagination:  29     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Depth Perception
Discrimination (Psychology) / physiology*
Form Perception / physiology*
Humans
Motion Perception / physiology*
Pattern Recognition, Visual / physiology*
Psychophysics
Grant Support
ID/Acronym/Agency:
EY07556/EY/NEI NIH HHS; EY13312/EY/NEI NIH HHS; R01 EY007556/EY/NEI NIH HHS; R01 EY007556-21/EY/NEI NIH HHS; R01 EY013312/EY/NEI NIH HHS; R01 EY013312-09/EY/NEI NIH HHS
Comments/Corrections

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