Human fall detection using machine vision techniques on RGB–D images-Reference-Cited by-同舟云学术

Human fall detection using machine vision techniques on RGB–D images

Published:2018-07 Issue: Volume:44 Page:146-153
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Panahi Leila,Ghods Vahid^ORCID

Publisher

Elsevier BV

Subject

Health Informatics,Signal Processing

Reference21 articles.

1. Evaluation of quality of life of the elderly population covered by healthcare centers of marivan and the influencing demographic and background factors in 2010;Farzianpour;Iran Red Crescent Med. J.,2012

2. Home safety, accessibility, and elderly health: evidence from falls;Eriksena;J. Urban Econ.,2015

3. Feature selection to detect fallen pose using depth images;Maldonado,2016

4. Human fall detection on embedded platform using depth maps and wireless accelerometer;Kwolek;Comput. Methods Programs Biomed.,2014

5. An online one class support vector machine-based person-specific fall detection system for monitoring an elderly individual in a room environment;Yu;IEEE J. Biomed. Health Inf.,2013

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