Fall detection system in enclosed environments based on single Gaussian model

被引：0

作者：

Adel Rhuma

Jonathon A Chambers

机构：

[1] AdvancedSignalProcessingGroup,DeptofElectronicandElectricalEngineering,LoughboroughUniversity,Loughborough

来源：

Journal of Measurement Science and Instrumentation | 2012年 / 3卷 / 02期

关键词：

humans fall detection; enclosed environments; one class support vector machine(OCSVM); imperfect training data; shape analysis; maximum likelihood(ML); background subtraction; codebook; voxel person;

D O I：

暂无

中图分类号：

TP391.41 [];

学科分类号：

080203 ;

摘要：

In this paper,we propose an efficient fall detection system in enclosed environments based on single Gaussian model using the maximum likelihood method.Online video clips are used to extract the features from two cameras.After the model is constructed,a threshold is set,and the probability for an incoming sample under the single Gaussian model is compared with that threshold to make a decision.Experimental results show that if a proper threshold is set,a good recognition rate for fall activities can be achieved.

引用

页码：123 / 128

页数：6

共 8 条

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