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People Counting in Videos by Fusing Temporal Cues from Spatial Context-Aware Convolutional Neural Networks

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Inteligencia Artificial Aplicada (GIAA)es
dc.contributor.authorSourtzinos, Panos
dc.contributor.authorVelastin Carroza, Sergio Alejandro
dc.contributor.authorJara, Miguel
dc.contributor.authorZegers, Pablo
dc.contributor.authorMakris, Dimitrios
dc.date.accessioned2019-10-02T07:36:48Z
dc.date.available2019-10-02T07:36:48Z
dc.date.issued2016-11-03
dc.descriptionThis paper has been presented at : 14th European Conference on Computer Visionen
dc.description.abstractWe present an efficient method for people counting in video sequences from fixed cameras by utilising the responses of spatially context-aware convolutional neural networks (CNN) in the temporal domain. For stationary cameras, the background information remains fairly static, while foreground characteristics, such as size and orientation may depend on their image location, thus the use of whole frames for training a CNN improves the differentiation between background and foreground pixels. Foreground density representing the presence of people in the environment can then be associated with people counts. Moreover the fusion, of the responses of count estimations, in the temporal domain, can further enhance the accuracy of the final count. Our methodology was tested using the publicly available Mall dataset and achieved a mean deviation error of 0.091.en
dc.format.extent13
dc.identifier.bibliographicCitationSourtzinos, P., Velastin, S.A., Jara, M., Zegers, P. y Makris, D. (2016). People Counting in Videos by Fusing Temporal Cues from Spatial Context-Aware Convolutional Neural Networks. In European Conference on Computer Vision 2016 Workshops, Part II, LNCS 9914, pp. 655–667.en
dc.identifier.doihttps://doi.org/10.1007/978-3-319-48881-3_46
dc.identifier.isbn978-3-319-48880-6
dc.identifier.publicationfirstpage655
dc.identifier.publicationlastpage667
dc.identifier.publicationtitleComputer Vision - ECCV 2016 Workshopsen
dc.identifier.publicationvolume9914
dc.identifier.urihttps://hdl.handle.net/10016/28944
dc.identifier.uxxiCC/0000029988
dc.language.isoengen
dc.publisherSpringeren
dc.relation.eventdate08-16 October 2016en
dc.relation.eventplaceAmsterdam, The Netherlandsen
dc.relation.eventtitle14th European Conference on Computer Vision 2016 Workshopen
dc.rights© Springer International Publishing Switzerland 2016en
dc.rights.accessRightsopen accessen
dc.subject.ecienciaInformáticaes
dc.subject.otherPeople countingen
dc.subject.otherConvolutional neural networkses
dc.subject.otherVideo analysisen
dc.titlePeople Counting in Videos by Fusing Temporal Cues from Spatial Context-Aware Convolutional Neural Networksen
dc.typeconference paper*
dc.type.hasVersionAM*
dspace.entity.typePublication
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