Fall detection based on skeleton extraction

This paper presents an improved skeleton extraction from depth video for fall detection based on fast randomized decision forest (RDF) algorithm. Due to the human's body orientation changes dramatically during falling, it reduces the accuracy of tracking. The human's orientation needs to b...

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Main Authors:	Chau, Lap-Pui, Bian, Zhen-Peng, Magnenat-Thalmann, Nadia
Other Authors:	School of Electrical and Electronic Engineering
Format:	Conference or Workshop Item
Language:	English
Published:	2013
Subjects:	DRNTU::Engineering::Electrical and electronic engineering
Online Access:	https://hdl.handle.net/10356/99395 http://hdl.handle.net/10220/12824
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-99395
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spelling	sg-ntu-dr.10356-993952020-03-07T12:48:41Z Fall detection based on skeleton extraction Chau, Lap-Pui Bian, Zhen-Peng Magnenat-Thalmann, Nadia School of Electrical and Electronic Engineering International Conference on Virtual-Reality Continuum and its Applications in Industry (11th : 2012 : Singapore) DRNTU::Engineering::Electrical and electronic engineering This paper presents an improved skeleton extraction from depth video for fall detection based on fast randomized decision forest (RDF) algorithm. Due to the human's body orientation changes dramatically during falling, it reduces the accuracy of tracking. The human's orientation needs to be corrected before the process by RDF. A rotation to correct the orientation is required frame by frame. Experimental results show that with the help of correction our proposed fall detection method could outperform the existing RDF based method. 2013-08-02T02:44:00Z 2019-12-06T20:06:45Z 2013-08-02T02:44:00Z 2019-12-06T20:06:45Z 2012 2012 Conference Paper Bian, Z. P., Chau, L. P., & Magnenat-Thalmann, N. (2012). Fall detection based on skeleton extraction. Proceedings of the 11th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry - VRCAI '12, 91-94. https://hdl.handle.net/10356/99395 http://hdl.handle.net/10220/12824 10.1145/2407516.2407544 en
institution	Nanyang Technological University
building	NTU Library
country	Singapore
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Electrical and electronic engineering
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering Chau, Lap-Pui Bian, Zhen-Peng Magnenat-Thalmann, Nadia Fall detection based on skeleton extraction
description	This paper presents an improved skeleton extraction from depth video for fall detection based on fast randomized decision forest (RDF) algorithm. Due to the human's body orientation changes dramatically during falling, it reduces the accuracy of tracking. The human's orientation needs to be corrected before the process by RDF. A rotation to correct the orientation is required frame by frame. Experimental results show that with the help of correction our proposed fall detection method could outperform the existing RDF based method.
author2	School of Electrical and Electronic Engineering
author_facet	School of Electrical and Electronic Engineering Chau, Lap-Pui Bian, Zhen-Peng Magnenat-Thalmann, Nadia
format	Conference or Workshop Item
author	Chau, Lap-Pui Bian, Zhen-Peng Magnenat-Thalmann, Nadia
author_sort	Chau, Lap-Pui
title	Fall detection based on skeleton extraction
title_short	Fall detection based on skeleton extraction
title_full	Fall detection based on skeleton extraction
title_fullStr	Fall detection based on skeleton extraction
title_full_unstemmed	Fall detection based on skeleton extraction
title_sort	fall detection based on skeleton extraction
publishDate	2013
url	https://hdl.handle.net/10356/99395 http://hdl.handle.net/10220/12824
_version_	1681034660228890624

Fall detection based on skeleton extraction

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