Human action recognition with line and flow histograms

dc.contributor.authorİkizler, Nazlıen_US
dc.contributor.authorCinbiş, R. Gökberken_US
dc.contributor.authorDuygulu, Pınaren_US
dc.coverage.spatialTampa, FL, USA
dc.date.accessioned2016-02-08T11:36:04Z
dc.date.available2016-02-08T11:36:04Z
dc.date.issued2008-12en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionDate of Conference: 8-11 Dec. 2008
dc.descriptionConference name: 19th International Conference on Pattern Recognition, 2008
dc.description.abstractWe present a compact representation for human action recognition in videos using line and optical flow histograms. We introduce a new shape descriptor based on the distribution of lines which are fitted to boundaries of human figures. By using an entropy-based approach, we apply feature selection to densify our feature representation, thus, minimizing classification time without degrading accuracy. We also use a compact representation of optical flow for motion information. Using line and flow histograms together with global velocity information, we show that high-accuracy action recognition is possible, even in challenging recording conditions. © 2008 IEEE.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T11:36:04Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2008en
dc.identifier.doi10.1109/ICPR.2008.4761434en_US
dc.identifier.urihttp://hdl.handle.net/11693/26795en_US
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttps://doi.org/10.1109/ICPR.2008.4761434
dc.source.title19th International Conference on Pattern Recognition, 2008en_US
dc.subjectAction recognitionen_US
dc.subjectClassification timeen_US
dc.subjectCompact representationen_US
dc.subjectFeature representationen_US
dc.subjectFeature selectionen_US
dc.subjectHigh-accuracyen_US
dc.subjectHuman-action recognitionen_US
dc.subjectMotion informationen_US
dc.subjectShape descriptorsen_US
dc.subjectVelocity informationen_US
dc.subjectGesture recognitionen_US
dc.subjectGraphic methodsen_US
dc.subjectOptical flowsen_US
dc.subjectFeature extractionen_US
dc.titleHuman action recognition with line and flow histogramsen_US
dc.typeConference Paperen_US

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