Intelligent detection of the falls in the elderly using fuzzy inference system and video-based motion estimation method

K. Rezaee, J. Haddadnia, A. Delbari
{"title":"Intelligent detection of the falls in the elderly using fuzzy inference system and video-based motion estimation method","authors":"K. Rezaee, J. Haddadnia, A. Delbari","doi":"10.1109/IRANIANMVIP.2013.6779996","DOIUrl":null,"url":null,"abstract":"Automatic detection of the abnormal walking in people, especially such accidents as the falls in the elderly, based on image processing techniques and computer vision can help develop an efficient system that its implementation in various contexts enables us to monitor people's movements. This paper proposes a new algorithm, which drawing on fuzzy rules in classification of movements as well as the implementation of the motion estimation, allows the rapid processing of the input data. At the testing stage, 57425 video frames received from Mother Nursing Home in Farzanegan and the video sequences containing the falls of the elderly were used. The results show that the values of average accuracy (AAC), detection rate (DR) and false alarm rate (FAR) were at an acceptable level, respectively with 93%, 89% and 5%. Compared to the similar techniques, the implementation of the proposed system in nursing homes and residential areas allow the real time and intelligent monitoring of the people.","PeriodicalId":297204,"journal":{"name":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 8th Iranian Conference on Machine Vision and Image Processing (MVIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRANIANMVIP.2013.6779996","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

Automatic detection of the abnormal walking in people, especially such accidents as the falls in the elderly, based on image processing techniques and computer vision can help develop an efficient system that its implementation in various contexts enables us to monitor people's movements. This paper proposes a new algorithm, which drawing on fuzzy rules in classification of movements as well as the implementation of the motion estimation, allows the rapid processing of the input data. At the testing stage, 57425 video frames received from Mother Nursing Home in Farzanegan and the video sequences containing the falls of the elderly were used. The results show that the values of average accuracy (AAC), detection rate (DR) and false alarm rate (FAR) were at an acceptable level, respectively with 93%, 89% and 5%. Compared to the similar techniques, the implementation of the proposed system in nursing homes and residential areas allow the real time and intelligent monitoring of the people.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于模糊推理系统和基于视频的运动估计方法的老年人跌倒智能检测
基于图像处理技术和计算机视觉的人类异常行走的自动检测,特别是老年人跌倒等事故,可以帮助开发一种高效的系统,它在各种情况下的实施使我们能够监控人们的运动。本文提出了一种利用模糊规则进行运动分类和运动估计的新算法,可以快速处理输入数据。在测试阶段,使用了从Farzanegan的母亲养老院收到的57425个视频帧,以及包含老年人跌倒的视频序列。结果表明,平均准确率(AAC)、检出率(DR)和虚警率(FAR)分别为93%、89%和5%,均处于可接受水平。与同类技术相比,所提出的系统在养老院和住宅区的实施可以实现对人们的实时智能监控。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Automated lung CT image segmentation using kernel mean shift analysis A simple and efficient approach for 3D model decomposition MRI image reconstruction via new K-space sampling scheme based on separable transform Fusion of SPECT and MRI images using back and fore ground information Real time occlusion handling using Kalman Filter and mean-shift
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1