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dc.creatorPoularakis, S.en
dc.creatorBriassouli, A.en
dc.creatorKompatsiaris, I.en
dc.date.accessioned2015-11-23T10:45:59Z
dc.date.available2015-11-23T10:45:59Z
dc.date.issued2009
dc.identifier10.1109/WIAMIS.2009.5031426
dc.identifier.isbn9781424436101
dc.identifier.urihttp://hdl.handle.net/11615/32425
dc.description.abstractMotion analysis is an important component of surveillance,video annotation and many other applications. Current work focuses on the tracking of moving entities, the representation of their actions and the classification of sequences. A wide range of methods are available for the characterization and analysis of human activity. This work presents an original approach for the detailed characterization of activity in a video sequence. A novel framework for encoding and extracting representative, repeating segments of activities is presented, resulting in "Full Action Instances". We focus on the analysis of human activities, however the proposed algorithm can be extended to more general categories of action that containsrepetitive components, due to its general design. © 2009 IEEE.en
dc.source.urihttp://www.scopus.com/inward/record.url?eid=2-s2.0-70349282115&partnerID=40&md5=a9575d9bf5c24235a282a44e2c8e6f74
dc.subjectHuman activitiesen
dc.subjectMotion analysisen
dc.subjectOther applicationsen
dc.subjectVideo annotationsen
dc.subjectVideo sequencesen
dc.subjectWork Focusen
dc.subjectAlgorithmsen
dc.subjectForestryen
dc.subjectImage analysisen
dc.subjectMultimedia servicesen
dc.subjectMultimedia systemsen
dc.subjectSecurity systemsen
dc.subjectVideo recordingen
dc.subjectGesture recognitionen
dc.titleFull action instances for motion analysisen
dc.typeconferenceItemen


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