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dc.contributor.authorRodríguez Moreno, Itsaso
dc.contributor.authorMartínez Otzeta, José María
dc.contributor.authorSierra Araujo, Basilio ORCID
dc.contributor.authorIrigoyen Garbizu, Itziar
dc.contributor.authorRodríguez Rodríguez, Igor ORCID
dc.contributor.authorGoienetxea Urkizu, Izaro
dc.date.accessioned2020-12-11T13:16:55Z
dc.date.available2020-12-11T13:16:55Z
dc.date.issued2020-11-14
dc.identifier.citationApplied Sciences 10(22) : (2020) // Article ID 8075es_ES
dc.identifier.issn2076-3417
dc.identifier.urihttp://hdl.handle.net/10810/48949
dc.description.abstractfirst_page settings Open AccessArticle Using Common Spatial Patterns to Select Relevant Pixels for Video Activity Recognition by Itsaso Rodríguez-Moreno * [OrcID] , José María Martínez-Otzeta [OrcID] , Basilio Sierra [OrcID] , Itziar Irigoien , Igor Rodriguez-Rodriguez and Izaro Goienetxea [OrcID] Department of Computer Science and Artificial Intelligence, University of the Basque Country, Manuel Lardizabal 1, 20018 Donostia-San Sebastián, Spain * Author to whom correspondence should be addressed. Appl. Sci. 2020, 10(22), 8075; https://doi.org/10.3390/app10228075 Received: 1 October 2020 / Revised: 30 October 2020 / Accepted: 11 November 2020 / Published: 14 November 2020 (This article belongs to the Special Issue Advanced Intelligent Imaging Technology Ⅱ) Download PDF Browse Figures Abstract Video activity recognition, despite being an emerging task, has been the subject of important research due to the importance of its everyday applications. Video camera surveillance could benefit greatly from advances in this field. In the area of robotics, the tasks of autonomous navigation or social interaction could also take advantage of the knowledge extracted from live video recording. In this paper, a new approach for video action recognition is presented. The new technique consists of introducing a method, which is usually used in Brain Computer Interface (BCI) for electroencephalography (EEG) systems, and adapting it to this problem. After describing the technique, achieved results are shown and a comparison with another method is carried out to analyze the performance of our new approach.es_ES
dc.description.sponsorshipThis work has been partially funded by the Basque Government, Research Teams grant number IT900-16, ELKARTEK 3KIA project KK-2020/00049, and the Spanish Ministry of Science (MCIU), the State Research Agency (AEI), and the European Regional Development Fund (FEDER), grant number RTI2018-093337-B-I100 (MCIU/AEI/FEDER, UE). We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this research.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/RTI2018-093337-B-I100es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subjectvideo activity recognitiones_ES
dc.subjectcommon spatial patternses_ES
dc.subjecthistogram of optical flowes_ES
dc.titleUsing Common Spatial Patterns to Select Relevant Pixels for Video Activity Recognitiones_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.date.updated2020-11-26T14:11:10Z
dc.rights.holder2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).es_ES
dc.relation.publisherversionhttps://www.mdpi.com/2076-3417/10/22/8075/htmles_ES
dc.identifier.doi10.3390/app10228075
dc.departamentoesCiencia de la computación e inteligencia artificial
dc.departamentoeuKonputazio zientziak eta adimen artifiziala


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2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).