Classifying Behaviours in Videos with Recurrent Neural Networks

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dc.contributorInformática Industrial y Redes de Computadoreses_ES
dc.contributor.authorAbellan-Abenza, Javier-
dc.contributor.authorGarcia-Garcia, Alberto-
dc.contributor.authorOprea, Sergiu-
dc.contributor.authorIvorra-Piqueres, David-
dc.contributor.authorGarcia-Rodriguez, Jose-
dc.contributor.otherUniversidad de Alicante. Departamento de Tecnología Informática y Computaciónes_ES
dc.identifier.citationInternational Journal of Computer Vision and Image Processing. 2017, 7(4): 1-14. doi:10.4018/IJCVIP.2017100101es_ES
dc.identifier.issn2155-6997 (Print)-
dc.identifier.issn2155-6989 (Online)-
dc.description.abstractThis article describes how the human activity recognition in videos is a very attractive topic among researchers due to vast possible applications. This article considers the analysis of behaviors and activities in videos obtained with low-cost RGB cameras. To do this, a system is developed where a video is input, and produces as output the possible activities happening in the video. This information could be used in many applications such as video surveillance, disabled person assistance, as a home assistant, employee monitoring, etc. The developed system makes use of the successful techniques of Deep Learning. In particular, convolutional neural networks are used to detect features in the video images, meanwhile Recurrent Neural Networks are used to analyze these features and predict the possible activity in the video.es_ES
dc.description.sponsorshipThis work has been funded by the Spanish Government TIN2016-76515-R grant for the COMBAHO project, supported with Feder funds.es_ES
dc.publisherIGI Globales_ES
dc.rights© 2017, IGI Globales_ES
dc.subjectConvolutional Neural Networkses_ES
dc.subjectHuman Behavioures_ES
dc.subjectLong-Short Term Memoryes_ES
dc.subjectRecurrent Neural Networkses_ES
dc.subjectRGB-D Camerases_ES
dc.subject.otherArquitectura y Tecnología de Computadoreses_ES
dc.titleClassifying Behaviours in Videos with Recurrent Neural Networkses_ES
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