Automatic fall detection for elderly by using features extracted from skeletal data
dc.contributor.author | Davari, Amir | |
dc.contributor.author | Aydin, T | |
dc.contributor.author | Erdem, Tanju | |
dc.date.accessioned | 2016-06-30T12:33:36Z | |
dc.date.available | 2016-06-30T12:33:36Z | |
dc.date.issued | 2013 | |
dc.identifier.uri | http://hdl.handle.net/10679/4241 | |
dc.identifier.uri | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6718245 | |
dc.description | Due to copyright restrictions, the access to the full text of this article is only available via subscription. | |
dc.description.abstract | Automatic detection of unusual events such as falls is very important especially for elderly people living alone. Realtime detection of these events can reduce the health risks associated with a fall. In this paper, we propose a novel method for automatic detection of fall event by using depth cameras. Depth images generated by these cameras are used in computing the skeletal data of a person. Our contribution is to use features extracted from the skeletal data to form a strong set of features which can help us achieve an increased precision at low redundancy. Our findings indicate that our features, which are derived from skeletal data, are moderately powerful for detecting unusual events such as fall. | |
dc.description.sponsorship | Turk Telekom Argela | |
dc.language.iso | eng | en_US |
dc.publisher | IEEE | |
dc.relation.ispartof | Electronics, Computer and Computation (ICECCO), 2013 International Conference on | |
dc.rights | restrictedAccess | |
dc.title | Automatic fall detection for elderly by using features extracted from skeletal data | en_US |
dc.type | Conference paper | en_US |
dc.peerreviewed | yes | |
dc.publicationstatus | published | en_US |
dc.contributor.department | Özyeğin University | |
dc.contributor.authorID | (ORCID 0000-0002-8841-1642 & YÖK ID 45777) Erdem, Tanju | |
dc.contributor.ozuauthor | Erdem, Tanju | |
dc.identifier.startpage | 127 | |
dc.identifier.endpage | 130 | |
dc.identifier.wos | WOS:000336616500033 | |
dc.identifier.doi | 10.1109/ICECCO.2013.6718245 | |
dc.subject.keywords | Fall detection | |
dc.subject.keywords | Event detection | |
dc.identifier.scopus | SCOPUS:2-s2.0-84894115180 | |
dc.contributor.ozugradstudent | Davari, Amir | |
dc.contributor.authorMale | 2 | |
dc.relation.publicationcategory | Conference Paper - International - Institutional Academic Staff and Graduate Student |
Files in this item
Files | Size | Format | View |
---|---|---|---|
There are no files associated with this item. |
This item appears in the following Collection(s)
Share this page