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Research Article

Performance analysis of Remote Fall Stalking using Multiple Extraction Techniques

  • Paper ID 31
  • Volume 1, Issue 6
  • Pages 01-03
  • Published Online: November-December 2021
  • 60 Views
Open Access Peer Reviewed

Authors

  • Khabiya Priyanka1
  • Gupta Om2

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

Article Information

DOI
No DOI
Published Online
November-December 2021
Pages
01-03
Article Type
Research Article
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No DOI available for cross-reference

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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