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dc.contributor.author | Bosch Jorge, Marc | es_ES |
dc.contributor.author | Sánchez Salmerón, Antonio José | es_ES |
dc.contributor.author | Valera Fernández, Ángel | es_ES |
dc.contributor.author | Ricolfe Viala, Carlos | es_ES |
dc.date.accessioned | 2015-06-10T08:15:58Z | |
dc.date.available | 2015-06-10T08:15:58Z | |
dc.date.issued | 2014-12 | |
dc.identifier.issn | 0957-4174 | |
dc.identifier.uri | http://hdl.handle.net/10251/51457 | |
dc.description.abstract | Falls in elderly people are becoming an increasing healthcare problem, since life expectancy and the number of elderly people who live alone have increased over recent decades. If fall detection systems could be installed easily and economically in homes, telecare could be provided to alleviate this problem. In this paper we propose a low cost fall detection system based on a single wide-angle camera. Wide-angle cameras are used to reduce the number of cameras required for monitoring large areas. Using a calibrated video system, two new features based on the gravity vector are introduced for fall detection. These features are: angle between the gravity vector and the line from feet to head of the human and size of the upper body. Additionally, to differentiate between fall events and controlled lying down events the speed of changes in the features is also measured. Our experiments demonstrate that our system is 97% accurate for fall detection. (C) 2014 Elsevier Ltd. All rights reserved. | es_ES |
dc.description.sponsorship | This work was partially financed by Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad (Direccion General de Investigacion Cientifica y Tecnica, Ministerio de Economia y Competitividad) under the project DPI2013-44227-R. | en_EN |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Expert Systems with Applications | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Fall detection | es_ES |
dc.subject | Artificial vision | es_ES |
dc.subject | Feature selection | es_ES |
dc.subject | Feature extraction | es_ES |
dc.subject | New features based on gravity vector | es_ES |
dc.subject | Monocular camera | es_ES |
dc.subject | Wide-angle camera | es_ES |
dc.subject | Calibration | es_ES |
dc.subject | Low cost | es_ES |
dc.subject.classification | INGENIERIA DE SISTEMAS Y AUTOMATICA | es_ES |
dc.title | Fall detection based on the gravity vector using a wide-angle camera | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.eswa.2014.06.045 | |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//DPI2013-44227-R/ES/METODOLOGIA DE DISEÑO DE SISTEMAS BIOMECATRONICOS. APLICACION AL DESARROLLO DE UN ROBOT PARALELO HIBRIDO PARA DIAGNOSTICO Y REHABILITACION/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica | es_ES |
dc.description.bibliographicCitation | Bosch Jorge, M.; Sánchez Salmerón, AJ.; Valera Fernández, Á.; Ricolfe Viala, C. (2014). Fall detection based on the gravity vector using a wide-angle camera. Expert Systems with Applications. 41(17):7980-7986. https://doi.org/10.1016/j.eswa.2014.06.045 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://dx.doi.org/10.1016/j.eswa.2014.06.045 | es_ES |
dc.description.upvformatpinicio | 7980 | es_ES |
dc.description.upvformatpfin | 7986 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 41 | es_ES |
dc.description.issue | 17 | es_ES |
dc.relation.senia | 277104 | |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |