Discovering hierarchical motion structure

DC FieldValueLanguage
dc.contributor.authorGershman, Samuel J.
dc.contributor.authorTenenbaum, Joshua B.
dc.contributor.authorJaekel, Frank
dc.date.accessioned2021-12-23T16:10:59Z-
dc.date.available2021-12-23T16:10:59Z-
dc.date.issued2016
dc.identifier.issn00426989
dc.identifier.urihttps://osnascholar.ub.uni-osnabrueck.de/handle/unios/9488-
dc.description.abstractScenes filled with moving objects are often hierarchically organized: the motion of a migrating goose is nested within the flight pattern of its flock, the motion of a car is nested within the traffic pattern of other cars on the road, the motion of body parts are nested in the motion of the body. Humans perceive hierarchical structure even in stimuli with two or three moving dots. An influential theory of hierarchical motion perception holds that the visual system performs a ``vector analysis'' of moving objects, decomposing them into common and relative motions. However, this theory does not specify how to resolve ambiguity when a scene admits more than one vector analysis. We describe a Bayesian theory of vector analysis and show that it can account for classic results from dot motion experiments, as well as new experimental data. Our theory takes a step towards understanding how moving scenes are parsed into objects. (C) 2015 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipDeutsche Forschungsgemeinschaft (DFG)German Research Foundation (DFG) [JA 1878/1-1]; ONR MURIMURIOffice of Naval Research [N00014-07-1-0937]; IARPA ICARUS program; MIT Intelligence Initiative; NSF STC awardNational Science Foundation (NSF) [CCF-1231216]; We thank Ed Vul, Liz Spelke, Jeff Beck, Alex Pouget, Yair Weiss, Ted Adelson, Rick Born, and Peter Battaglia for helpful discussions. This work was supported by the Deutsche Forschungsgemeinschaft (DFG JA 1878/1-1), ONR MURI N00014-07-1-0937, IARPA ICARUS program, the MIT Intelligence Initiative, and the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216. A preliminary version of this work was presented at the 35th annual Cognitive Science Society meeting (Gershman, Jakel, & Tenenbaum, 2013).
dc.language.isoen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.relation.ispartofVISION RESEARCH
dc.subjectBayesian inference
dc.subjectINTEGRATION
dc.subjectMODEL
dc.subjectMotion perception
dc.subjectNeurosciences
dc.subjectNeurosciences & Neurology
dc.subjectOphthalmology
dc.subjectPERCEPTION
dc.subjectPsychology
dc.subjectSEGMENTATION
dc.subjectStructure learning
dc.titleDiscovering hierarchical motion structure
dc.typejournal article
dc.identifier.doi10.1016/j.visres.2015.03.004
dc.identifier.isiISI:000382712600021
dc.description.volume126
dc.description.issueSI
dc.description.startpage232
dc.description.endpage241
dc.identifier.eissn18785646
dc.publisher.placeTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
dcterms.isPartOf.abbreviationVision Res.
dcterms.oaStatusBronze
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