Fall Detection Based on Body Part Tracking Using a Depth Camera-Reference-Cited by-同舟云学术

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Fall Detection Based on Body Part Tracking Using a Depth Camera

Published:2015-03 Issue:2 Volume:19 Page:430-439
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Bian Zhen-Peng,Hou Junhui,Chau Lap-Pui,Magnenat-Thalmann Nadia

Funder

Institute for Media Innovation

Nanyang Technological University, Singapore

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Biotechnology

Link

http://xplorestaging.ieee.org/ielx7/6221020/7053969/06804646.pdf?arnumber=6804646

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1. Radar-Based Fall Detection: A Survey [Survey];IEEE Robotics & Automation Magazine;2024-09

2. XFall: Domain Adaptive Wi-Fi-Based Fall Detection With Cross-Modal Supervision;IEEE Journal on Selected Areas in Communications;2024-09

3. Visual Fall Detection Analysis Through Computer Vision and Deep Learning – Technology Proposition;International Journal of Recent Technology and Engineering (IJRTE);2024-05-30

4. SIMFALL: A Data Generator for RF-Based Fall Detection;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

5. Multimodal fall detection for solitary individuals based on audio-video decision fusion processing;Heliyon;2024-04

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