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dc.contributor.authorKühne, Hildegard*
dc.date.accessioned2021-02-11T08:09:52Z
dc.date.available2021-02-11T08:09:52Z
dc.date.issued2014*
dc.date.submitted2019-07-30 20:02:01*
dc.identifier35287*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/40815
dc.description.abstractThis work focuses the recognition of complex human activities in video data. A combination of new features and techniques from speech recognition is used to realize a recognition of action units and their combinations in video sequences. The presented approach shows how motion information gained from video data can be used to interpret the underlying structural information of actions and how higher level models allow an abstraction of different motion categories beyond simple classification.*
dc.languageEnglish*
dc.subjectQA75.5-76.95*
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UY Computer scienceen_US
dc.subject.otherVideoanalyse*
dc.subject.othermotion features*
dc.subject.othergenerative ModelleAction recognition*
dc.subject.othergenerative models*
dc.subject.otherBewegungsmerkmale*
dc.subject.otherBewegungserkennung*
dc.subject.othervideo analysis*
dc.titleAnalysis and recognition of human actions with flow features and temporal models*
dc.typebook
oapen.identifier.doi10.5445/KSP/1000043583*
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2*
oapen.relation.isbn9783731502821*
oapen.pagesXV, 183 p.*
peerreview.review.typeFull text
peerreview.anonymityAll identities known
peerreview.reviewer.typeInternal editor
peerreview.reviewer.typeExternal peer reviewer
peerreview.review.stagePre-publication
peerreview.open.reviewNo
peerreview.publish.responsibilityScientific or Editorial Board
peerreview.id8ad5c235-9810-49eb-b358-27c8675324d9
peerreview.titleDissertations (Dissertationen)


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