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Research Article

Performance analysis of Remote Fall Stalking using Multiple Extraction Techniques

Khabiya Priyanka1 Gupta Om2
1,2Dept. of EEE, Laxmi Bai Sahuji Institute of Engineering & Technology, MP, India.

Published Online: November-December 2021

Pages: 01-03

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References

1.SubhashChandAgrawal;RajeshKumarTripathi;AnandSinghJalal,―Human fall detection from an indoor video surveillance‖, 2017
8thInternationalConferenceonComputing,CommunicationandNetworkingTechnologies(ICCCNT), Pages 1-5, 2017
2.OluwatoyinP.Popoola;Kejun Wang,―Video-BasedAbnormalHuman BehaviorRecognition—AReview‖IEEETransactionsOnSystems,Man,
And Cybernetics—Part C: Applications And Reviews, Vol. 42,No. 6,November2012
3.G M Basavaraj; Ashok Kusagur, ‖Vision based surveillance system fordetection of human fall‖, 2nd IEEE International Conference on
RecentTrendsinElectronics,Information&CommunicationTechnology(RTEICT), Pages 1516-1520,2017
4.Zhen-PengBian ; JunhuiHou ; Lap-PuiChau ; NadiaMagnenat-Thalmann, ―Fall Detection Based on Body Part Tracking
UsingaDepthCamera‖,IEEEJournalofBiomedicalandHealthInformatics,
5.XinMa;HaiboWang;BingxiaXue,MingangZhou;BingJi,andYibinLi, ―Depth-Based Human Fall Detection via Shape Features and
Improved Extreme Learning Machine, IEEE Journal Of BiomedicalAnd Health Informatics,Vol. 18, No.6, November2014
6.LesyaAnishchenko,―Machinelearningin videosurveillanceforfall detection",UralSymposiumonBiomedicalEngineering,Radioelectronics
and Information Technology (USBEREIT), Pages 99-102,2018

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