Analysis and recognition of human actions with flow features and temporal models

dc.creator	Hildegard, Kühne
dc.date.accessioned	2021-01-20T20:22:50Z
dc.date.available	2021-01-20T20:22:50Z
dc.date.created	2014
dc.description.abstractenglish	This 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.	spa
dc.format.extent	208 páginas	spa
dc.format.mimetype	application/pdf	spa
dc.identifier.doi	10.5445/KSP/1000043583
dc.identifier.isbn	978-3-731-50282-1
dc.identifier.other	https://www.ksp.kit.edu/9783731502821
dc.identifier.uri	https://hdl.handle.net/20.500.12010/16791
dc.language.iso	eng	spa
dc.publisher	KIT Scientific Publishing	spa
dc.rights.accessrights	info:eu-repo/semantics/openAccess	spa
dc.rights.creativecommons	https://creativecommons.org/licenses/by-sa/4.0/legalcode
dc.rights.local	Abierto (Texto Completo)	spa
dc.subject	Ciencias de la computación	spa
dc.subject.lemb	Reconocimiento de voz	spa
dc.subject.lemb	Video	spa
dc.subject.lemb	Video analysis	spa
dc.title	Analysis and recognition of human actions with flow features and temporal models	spa
dc.type.coar	http://purl.org/coar/resource_type/c_2f33	spa

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Nombre:: Analysis and recognition of human actions with flow features and temporal models_64.pdf
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