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Mid-level feature set for specific event and anomaly detection in crowded scenes

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dc.affiliation.dptoUC3M. Departamento de Teoría de la Señal y Comunicacioneses
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Procesado Multimediaes
dc.contributor.authorCalle Silos, Fernando de laes
dc.contributor.authorGonzález Díaz, Ivánes
dc.contributor.authorDíaz de María, Fernandoes
dc.date.accessioned2015-09-18T10:32:56Z
dc.date.available2015-09-18T10:32:56Z
dc.date.issued2013
dc.descriptionProceedings of: 20th IEEE International Conference on Image Processing (ICIP 2013). Melbourne, Australia, September 15-18, 2013.en
dc.description.abstractIn this paper we propose a system for automatic detection of specific events and abnormal behaviors in crowded scenes. In particular, we focus on the parametrization by proposing a set of mid-level spatio-temporal features that successfully model the characteristic motion of typical events in crowd behaviors. Furthermore, due to the fact that some features are more suitable than others to model specific events of interest, we also present an automatic process for feature selection. Our experiments prove that the suggested feature set works successfully for both explicit event detection and distance-based anomaly detection tasks. The results on PETS for explicit event detection are generally better than those previously reported. Regarding anomaly detection, the proposed method performance is comparable to those of state-of-the-art method for PETS and substantially better than that reported for Web dataset.en
dc.description.statusPublicadoes
dc.format.extent5
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitation2013 IEEE International Conference on Image Processing ICIP 2013: Proceedings. (pp. 4001 - 4005). IEEE.en
dc.identifier.doi10.1109/ICIP.2013.6738824
dc.identifier.isbn978-1-4799-2341-0
dc.identifier.publicationfirstpage4001
dc.identifier.publicationlastpage4005
dc.identifier.publicationtitle2013 IEEE International Conference on Image Processing ICIP 2013: Proceedings.en
dc.identifier.urihttps://hdl.handle.net/10016/21587
dc.identifier.uxxiCC/0000022142
dc.language.isoengen
dc.publisherIEEEen
dc.relation.eventdateSeptember 15-18, 2013.en
dc.relation.eventnumber20
dc.relation.eventplaceMelbourne, Australiaen
dc.relation.eventtitle20th IEEE International Conference on Image Processing (ICIP 2013).en
dc.relation.publisherversionhttp://dx.doi.org/10.1109/ICIP.2013.6738824es
dc.rights© 2013 IEEE.en
dc.rights.accessRightsopen accessen
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherClutter environmenten
dc.subject.otherCrowded environmentsen
dc.subject.otherMachine Visionen
dc.subject.otherMotion analysisen
dc.subject.otherVideo processingen
dc.subject.otherVideo surveillanceen
dc.titleMid-level feature set for specific event and anomaly detection in crowded scenesen
dc.typeconference paper*
dc.type.hasVersionAM*
dspace.entity.typePublication
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