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A new framework for elderly fall detection using coupled hidden markov models
Joint Authors
Mahjub, Muhammad
Haji, Mabruk
al-Ayib, Faysal
Source
The International Arab Journal of Information Technology
Issue
Vol. 16, Issue 4 (31 Jul. 2019)9 p.
Publisher
Publication Date
2019-07-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Falls are a most common problem for old people.
They can result in dangerous consequences even death.
Many recent works have presented different approaches to detect fall and prevent dangerous outcomes.
In this paper, human fall detection from video streams based on a coupled Hidden Markov Model (CHMM) has been proposed.
The CHMM was used to model the motion and static spatial characteristic of human silhouette.
The validity of current proposed method was demonstrated with experiments on Le2i database, Weizman database and video from Youtube simulating falls and normal activities.
Experimental results showed the superiority of the CHMM for video fall detection.
American Psychological Association (APA)
Haji, Mabruk& Mahjub, Muhammad& al-Ayib, Faysal. 2019. A new framework for elderly fall detection using coupled hidden markov models. The International Arab Journal of Information Technology،Vol. 16, no. 4.
https://search.emarefa.net/detail/BIM-854848
Modern Language Association (MLA)
Haji, Mabruk…[et al.]. A new framework for elderly fall detection using coupled hidden markov models. The International Arab Journal of Information Technology Vol. 16, no. 4 (Jul. 2019).
https://search.emarefa.net/detail/BIM-854848
American Medical Association (AMA)
Haji, Mabruk& Mahjub, Muhammad& al-Ayib, Faysal. A new framework for elderly fall detection using coupled hidden markov models. The International Arab Journal of Information Technology. 2019. Vol. 16, no. 4.
https://search.emarefa.net/detail/BIM-854848
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-854848