Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/7606

Title: A robust fall detection system for the elderly in a smart room
Authors: Yu, Miao
Naqvi, Syed M.R.
Chambers, Jonathon
Keywords: Code-book background subtraction
Density method
Fall detection
Head tracking
Motion-based particle filtering
Issue Date: 2010
Publisher: © IEEE
Citation: YU, M., NAQVI, S.M. and CHAMBERS, J., 2010. A robust fall detection system for the elderly in a smart room. IN: IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), Dallas, TX, 14-19 March, pp.1666-1669
Abstract: In this paper, we propose a novel and robust fall detection system by using a density method for modeling a fall event as a function of certain video feature.3-D head velocity and human shape information are extracted as feature and three types of density model, single Gaussian, mixture of Gaussians and Parzen window method, are constructed for modeling the density of fall with respect to the extracted video feature. Falls are then detected according to the corresponding obtained density model and the success of the method is confirmed on real video sequences.
Description: This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
DOI: 10.1109/ICASSP.2010.5495512
URI: https://dspace.lboro.ac.uk/2134/7606
Publisher Link: http://dx.doi.org/10.1109/ICASSP.2010.5495512
ISBN: 9781424442959
Appears in Collections:Conference Papers and Presentations (Mechanical, Electrical and Manufacturing Engineering)

Files associated with this item:

File Description SizeFormat
naqvi2.pdf198.85 kBAdobe PDFView/Open


SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.