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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/5550

Title: Fall detection in the elderly by head tracking
Authors: Yu, Miao
Naqvi, Syed M.
Chambers, Jonathon
Keywords: Motion history image
Code-book background subtraction
Particle filtering
Head tracking
Fall detection
Issue Date: 2009
Publisher: © IEEE
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.
Abstract: In 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.
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/SSP.2009.5278566
URI: https://dspace.lboro.ac.uk/2134/5550
Appears in Collections:Conference Papers and Contributions (Mechanical, Electrical and Manufacturing Engineering)

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