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Learned non-rigid object motion is a view-invariant cue to recognizing novel objects

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dc.contributor.authorChuang, Lewis L.-
dc.contributor.authorVuong, Quoc C.-
dc.contributor.authorBuelthoff, Heinrich H.-
dc.date.accessioned2021-09-06T19:44:36Z-
dc.date.available2021-09-06T19:44:36Z-
dc.date.created2021-06-18-
dc.date.issued2012-05-22-
dc.identifier.issn1662-5188-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/108404-
dc.description.abstractThere is evidence that observers use learned object motion to recognize objects. For instance, studies have shown that reversing the learned direction in which a rigid object rotated in depth impaired recognition accuracy. This motion reversal can be achieved by playing animation sequences of moving objects in reverse frame order. In the current study, we used this sequence-reversal manipulation to investigate whether observers encode the motion of dynamic objects in visual memory, and whether such dynamic representations are encoded in a way that is dependent on the viewing conditions. Participants first learned dynamic novel objects, presented as animation sequences. Following learning, they were then tested on their ability to recognize these learned objects when their animation sequence was shown in the same sequence order as during learning or in the reverse sequence order. In Experiment 1, we found that non-rigid motion contributed to recognition performance; that is, sequence-reversal decreased sensitivity across different tasks. In subsequent experiments, we tested there cognition of non-rigidly deforming (Experiment 2) and rigidly rotating (Experiment 3) objects across novel view points. Recognition performance was affected by view point changes for both experiments. Learned non-rigid motion continued to contribute to recognition performance and this benefit was the same across all view point changes. By comparison, learned rigid motion did not contribute to recognition performance. These results suggest that non-rigid motion provides a source of information for recognizing dynamic objects, which is not affected by changes to viewpoint.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherFRONTIERS MEDIA SA-
dc.subjectBIOLOGICAL MOTION-
dc.subjectFACIAL MOTION-
dc.subjectRECOGNITION-
dc.subjectPERCEPTION-
dc.subjectCORTEX-
dc.subjectMEMORY-
dc.subjectINFORMATION-
dc.subjectMECHANISMS-
dc.subjectDESIGNS-
dc.subjectSHAPE-
dc.titleLearned non-rigid object motion is a view-invariant cue to recognizing novel objects-
dc.typeArticle-
dc.contributor.affiliatedAuthorBuelthoff, Heinrich H.-
dc.identifier.doi10.3389/fncom.2012.00026-
dc.identifier.scopusid2-s2.0-84864940756-
dc.identifier.wosid000304263200001-
dc.identifier.bibliographicCitationFRONTIERS IN COMPUTATIONAL NEUROSCIENCE, v.6-
dc.relation.isPartOfFRONTIERS IN COMPUTATIONAL NEUROSCIENCE-
dc.citation.titleFRONTIERS IN COMPUTATIONAL NEUROSCIENCE-
dc.citation.volume6-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaMathematical & Computational Biology-
dc.relation.journalResearchAreaNeurosciences & Neurology-
dc.relation.journalWebOfScienceCategoryMathematical & Computational Biology-
dc.relation.journalWebOfScienceCategoryNeurosciences-
dc.subject.keywordPlusBIOLOGICAL MOTION-
dc.subject.keywordPlusFACIAL MOTION-
dc.subject.keywordPlusRECOGNITION-
dc.subject.keywordPlusPERCEPTION-
dc.subject.keywordPlusCORTEX-
dc.subject.keywordPlusMEMORY-
dc.subject.keywordPlusINFORMATION-
dc.subject.keywordPlusMECHANISMS-
dc.subject.keywordPlusDESIGNS-
dc.subject.keywordPlusSHAPE-
dc.subject.keywordAuthorvisual object recognition-
dc.subject.keywordAuthormotion-
dc.subject.keywordAuthorspatio-temporal signature-
dc.subject.keywordAuthornon-rigid motion-
dc.subject.keywordAuthorreversal effect-
dc.subject.keywordAuthorview-dependency-
dc.subject.keywordAuthorrigid motion-
dc.subject.keywordAuthordepth rotation-
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