Fall detection based on skeleton extraction

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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Bibliographic Details
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
Description
Summary: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.

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