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Fuzzy model for human fall detection in infrared video

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dc.contributor.author Castillo Montoya, José Carlos es_ES
dc.contributor.author Fernández Caballero, Antonio es_ES
dc.contributor.author Sokolova, Marina es_ES
dc.contributor.author Serrano Cuerda, Juan es_ES
dc.date.accessioned 2014-03-06T07:10:26Z
dc.date.available 2014-03-06T07:10:26Z
dc.date.issued 2013 es_ES
dc.identifier.citation Journal of intelligent & fuzzy systems, 2013, 24: 215-228 es_ES
dc.identifier.issn 1064-1246 es_ES
dc.identifier.uri http://hdl.handle.net/10578/3698
dc.description.abstract Fall detection, especially for elderly people, is a challenging problem which demands new products and technologies. In this paper a fuzzy model for fall detection and inactivity monitoring in infrared video is presented. The classification features proposed include geometric and kinematic parameters associated with more or less sudden changes in the tracked human-related regions of interest. A complete segmentation and tracking algorithm for infrared video as well as a fuzzy fall detection and confirmation algorithm are introduced. The proposed system is capable of identifying true and false falls, enhanced with inactivity monitoring aimed at confirming the need for medical assistance and/or care. The fall indicators used as well as their fuzzy model is explained in detail. The fuzzy model has been tested for a wide number of static and dynamic falls, demonstrating exciting initial results. es_ES
dc.format text/plain en_US
dc.language.iso es en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Ingenierías es_ES
dc.title Fuzzy model for human fall detection in infrared video es_ES
dc.type info:eu-repo/semantics/article en_US

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