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dc.contributor.authorDuque Domingo, Jaime
dc.contributor.authorGómez García-Bermejo, Jaime 
dc.contributor.authorZalama Casanova, Eduardo 
dc.contributor.authorCerrada, Carlos
dc.contributor.authorValero, Enrique
dc.date.accessioned2021-09-01T11:29:20Z
dc.date.available2021-09-01T11:29:20Z
dc.date.issued2019
dc.identifier.citationSensors, 2019, vol. 19, n. 24, 5495es
dc.identifier.issn1424-8220es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/48465
dc.descriptionProducción Científicaes
dc.description.abstractThis work presents an integrated Indoor Positioning System which makes use of WiFi signals and RGB cameras, such as surveillance cameras, to track and identify people navigating in complex indoor environments. Previous works have often been based on WiFi, but accuracy is limited. Other works use computer vision, but the problem of identifying concrete persons relies on such techniques as face recognition, which are not useful if there are many unknown people, or where the robustness decreases when individuals are seen from different points of view. The solution presented in this paper is based on an accurate combination of smartphones along with RGB cameras, such as those used in surveillance infrastructures. WiFi signals from smartphones allow the persons present in the environment to be identified uniquely, while the data coming from the cameras allow the precision of location to be improved. The system is nonintrusive, and biometric data about subjects is not required. In this paper, the proposed method is fully described and experiments performed to test the system are detailed along with the results obtained.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherMDPIes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.classificationIndoor positioninges
dc.subject.classificationPosicionamiento en interioreses
dc.subject.classificationRGB camerases
dc.subject.classificationCámaras RGBes
dc.subject.classificationWiFies
dc.subject.classificationWireless networkses
dc.subject.classificationRedes inalámbricases
dc.titleIntegration of Computer Vision and Wireless Networks to Provide Indoor Positioninges
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2019 MDPIes
dc.identifier.doi10.3390/s19245495es
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/19/24/5495es
dc.peerreviewedSIes
dc.description.projectMinisterio de Ciencia, Innovación y Universidades (grant RTI2018-096652-B-I00)es
dc.description.projectJunta de Castilla y León (grant VA233P18)es
dc.description.projectMinisterio de Economía, Industria y Competitividad (project DPI2016-77677-P)es
dc.description.projectComunidad de Madrid (project S2018/NMT-4331)es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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