New Fast Fall Detection Method Based on Spatio-Temporal Context Tracking of Head by Using Depth Images

In order to deal with the problem of projection occurring in fall detection with two-dimensional (2D) grey or color images, this paper proposed a robust fall detection method based on spatio-temporal context tracking over three-dimensional (3D) depth images that are captured by the Kinect sensor. In...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 15; H. 9; S. 23004 - 23019
Hauptverfasser:	Yang, Lei, Ren, Yanyun, Hu, Huosheng, Tian, Bo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 11.09.2015 MDPI
Schlagworte:	Accidental Falls Adult Algorithms Computer engineering Dense spatio-temporal-context depth images fall detection Falls Head - physiology Home environment Human subjects Humans Image detection Imaging, Three-Dimensional - methods Mathematical analysis Methods Older people Planes Sensors Single-Gauss-Model Three dimensional Tracking Two dimensional United States > US China depth images Single-Gauss-Model Dense spatio-temporal-context fall detection
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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