Fall detection in the elderly by head tracking.pdf (341.58 kB)
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conference contribution
posted on 2009-12-01, 15:28 authored by Miao Yu, Syed M.R. Naqvi, Jonathon ChambersIn the paper, we propose a fall detection method based
on head tracking within a smart home environment equipped
with video cameras. A motion history image and code-book
background subtraction are combined to determine whether
large movement occurs within the scene. Based on the magnitude
of the movement information, particle filters with different
state models are used to track the head. The head
tracking procedure is performed in two video streams taken
by two separate cameras and three-dimensional head position
is calculated based on the tracking results. Finally, the threedimensional
horizontal and vertical velocities of the head are
used to detect the occurrence of a fall. The success of the
method is confirmed on real video sequences.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Citation
YU, M., NAQVI, S.M. and CHAMBERS, J.A., 2009. Fall detection in the elderly by head tracking. IN: IEEE Workshop on Statistical Signal Processing (SSP2009), Cardiff, Wales, 31 August-3 September, pp. 320-325.Publisher
© IEEEVersion
- VoR (Version of Record)
Publication date
2009Notes
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.Language
- en