Linked Life Data

21047747

Source:http://linkedlifedata.com/resource/pubmed/id/21047747

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2010-11-4
pubmed:abstractText
Among the most common events in our daily lives is seeing people in action. Scientists have accumulated evidence suggesting humans may have developed specialized mechanisms for recognizing these visual events. In the current experiments, we apply the "bubbles" technique to construct space-time classification movies that reveal the key features human observers use to discriminate biological motion stimuli (point-light and stick figure walkers). We find that observers rely on similar features for both types of stimuli, namely, form information in the upper body and dynamic information in the relative motion of the limbs. To measure the contributions of motion and form analyses in this task, we computed classification movies from the responses of a biologically plausible model that can discriminate biological motion patterns (M. A. Giese & T. Poggio, 2003). The model classification movies reveal similar key features to observers, with the model's motion and form pathways each capturing unique aspects of human performance. In a second experiment, we computed classification movies derived from trials of varying exposure times (67-267 ms) and demonstrate the transition to form-based strategies as motion information becomes less available. Overall, these results highlight the relative contributions of motion and form computations to biological motion perception.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1534-7362
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
10
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
15
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Perceptual and computational analysis of critical features for biological motion.
pubmed:affiliation
Department of Cognitive Science, Center for Cognitive Neuroscience, University of California, Irvine, USA. sthurman@uci.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.