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A Bag of Expression Framework for Improved Human Action Recognition

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Inteligencia Artificial Aplicada (GIAA)es
dc.contributor.authorNazir, Saima
dc.contributor.authorYousaf, Muhammad Haroon
dc.contributor.authorNebel, Jean-Christophe
dc.contributor.authorVelastin Carroza, Sergio Alejandro
dc.date.accessioned2018-05-07T11:51:23Z
dc.date.available2020-02-01T00:00:04Z
dc.date.issued2018-02-01
dc.description.abstractThe Bag of Words (BoW) approach has been widely used for human action recognition in recent state-of-the-art methods. In this paper, we introduce what we call a Bag of Expression (BoE) framework, based on the bag of words method, for recognizing human action in simple and realistic scenarios. The proposed approach includes space time neighborhood information in addition to visual words. The main focus is to enhance the existing strengths of the BoW approach like view independence, scale invariance and occlusion handling. BOE includes independent pairs of neighbors for building expressions, therefore it is tolerant to occlusion and capable of handling view independence up to some extent in realistic scenarios. Our main contribution includes learning a class specific visual words extraction approach for establishing a relationship between these extracted visual words in both space and time dimension. Finally, we have carried out a set of experiments to optimize different parameters and compare its performance with recent state-of-the-art-methods. Our approach outperforms existing Bag of Words based approaches, when evaluated using the same performance evaluation methods. We tested our approach on four publicly available datasets for human action recognition i.e. UCF-Sports, KTH, UCF11 and UCF50 and achieve significant results i.e. 97.3%, 99.5%, 96.7% and 93.42% respectively in terms of average accuracy.en
dc.description.sponsorshipSergio A Velastin has received funding from the Universidad Carlos III de Madrid, the European Unions Seventh Framework Programme for research, technological development and demonstration under grant agreement nº 600371, el Ministerio de Economía, Industria y Competitividad (COFUND2013-51509) el Ministerio de Educación, Cultura y Deporte (CEI-15-17) and Banco Santander.en
dc.format.extent11
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationNazira, S., Yousafa, M.H., Nebel, J.C., Velastin, S.A.(2018). A Bag of Expression Framework for Improved Human Action Recognition. Pattern Recognition Letters, 103, pp. 39-45.en
dc.identifier.doihttps://doi.org/10.1016/j.patrec.2017.12.024
dc.identifier.issn0167-8655
dc.identifier.publicationfirstpage39
dc.identifier.publicationlastpage45
dc.identifier.publicationtitlePattern Recognition Lettersen
dc.identifier.publicationvolume103
dc.identifier.urihttps://hdl.handle.net/10016/26382
dc.identifier.uxxiAR/0000020832
dc.language.isoeng
dc.publisherElsevieres
dc.relation.projectIDGobierno de España. COFUND2013-51509es
dc.relation.projectIDGobierno de España. CEI-15-17es
dc.rights© Elsevier
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaInformáticaes
dc.subject.otherHuman action recognitionen
dc.subject.otherBag of wordsen
dc.subject.otherBag of visual wordsen
dc.titleA Bag of Expression Framework for Improved Human Action Recognitionen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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