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|Title: ||A robust fall detection system for the elderly in a smart room|
|Authors: ||Yu, Miao|
Naqvi, Syed M.
|Keywords: ||Code-book background subtraction|
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.|
|Publisher Link: ||http://dx.doi.org/10.1109/ICASSP.2010.5495512|
|Appears in Collections:||Conference Papers and Contributions (Mechanical, Electrical and Manufacturing Engineering)|
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