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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

Abstract

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Researchers have drew in with finding the best different choices. This includes wearable sensors, modernized thinking, etc. What is this paper about? It was to find the most effective way to manage beneficially distinguish a fall with fewer misdirecting alarms and was implemented by finding the Histogram of Oriented Gradients close by quantifiable methods which removes huge features and differentiated it and the trained videos. A coordinated learning strategy is exploited, where thedatabaseistrainedwithvideosthatcontainbothfallandquotidianactivities(QA).SupportVectorMachine(SVM)isutilizedindistinguishingfallanddailyevents.Thedoctor/supervisor isintimatedviaemailondetection of fall. Index terms: GMM,HOG, Real-time processing, Supervised Learning, Statistical feature, SVM

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  • ISSN 2583-1240
  • Open Access
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