A ROBUST FALL DETECTION SYSTEM FOR THE ELDERLY IN A SMART ROOM

被引：14

作者：

Yu, Miao ^{[1
]}

Naqvi, Syed Mohsen ^{[1
]}

Chambers, Jonathon ^{[1
]}

机构：

[1] Univ Loughborough, Elect & Elect Engn Dept, Adv Signal Proc Grp, Loughborough, Leics, England

来源：

2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING | 2010年

关键词：

code-book background subtraction; motion-based particle filtering; head tracking; density method; fall detection;

D O I：

10.1109/ICASSP.2010.5495512

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

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.

引用

页码：1666 / 1669

页数：4

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