Fall Detection using Human Skeleton Features

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dc.contributor.author Ramirez, Heilym
dc.contributor.author Velastin Carroza, Sergio Alejandro
dc.contributor.author Fabregas, Ernesto
dc.contributor.author Meza, Ignacio
dc.contributor.author Makris, Dimitrios
dc.contributor.author Farias, Gonzalo
dc.date.accessioned 2021-06-03T09:08:56Z
dc.date.available 2021-06-03T09:08:56Z
dc.date.issued 2021-03-17
dc.identifier.bibliographicCitation Ramirez, H., et al. (2021, march). Fall Detection using Human Skeleton Features. In: 11th International Conference on Pattern Recognition Systems (ICPRS-21), conference paper, 17-19 mar, 2021, Curicó, Chile.
dc.identifier.other http://www.icprs.org/
dc.identifier.uri http://hdl.handle.net/10016/32826
dc.description Procedings in: 11th International Conference on Pattern Recognition Systems (ICPRS-21), conference paper, 17-19 mar, 2021, Universidad de Talca, Curicó, Chile.
dc.description.abstract Falls is one of the leading causes of death and serious injury in people, especially the elderly. In addition, the falls accidents have a direct financial cost for health systems and, indirectly, for the productivity of society. Among the most important problems in fall detection systems is privacy, limitations of operating devices, and the comparison of machine learn-ing techniques for detection. This article presents a fall detection system by means of a k-Nearest Neighbor (KNN) classifier based on camera-vision using pose detection of the human skeleton for the features extraction. The proposed method is evaluated with UP-FALL dataset, surpassing on the results of other fall detection systems that use the same database. This method achieves a 98.84% accuracy andF1-Score of 97.41%.
dc.description.sponsorship This work was supported by the Chilean Research and Development Agency (ANID) under the Project FONDECYT 1191188.
dc.format.extent 6
dc.language.iso eng
dc.publisher IET Digital Library
dc.rights © Institution of Engineering and Technology, 2021.
dc.subject.other Fall detection
dc.subject.other Human skeleton
dc.subject.other Pose estimation
dc.subject.other Computer vision
dc.title Fall Detection using Human Skeleton Features
dc.type conferenceObject
dc.subject.eciencia Informática
dc.rights.accessRights openAccess
dc.type.version acceptedVersion
dc.relation.eventdate 2021-03-17
dc.relation.eventplace Universidad de Talca, Curicó, Chile (conferencia virtual)
dc.relation.eventtitle 11th International Conference on Pattern Recognition Systems (ICPRS-21)
dc.relation.eventtype proceeding
dc.identifier.publicationtitle Fall Detection using Human Skeleton Features
dc.identifier.uxxi CC/0000032477
dc.affiliation.dpto UC3M. Departamento de Informática
dc.affiliation.grupoinv UC3M. Grupo de Investigación: Inteligencia Artificial Aplicada (GIAA)
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