An Approach to Real-Time Fall Detection based on OpenPose and LSTM-Reference-Cited by-同舟云学术

An Approach to Real-Time Fall Detection based on OpenPose and LSTM

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)
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Author:

Chen Po-Chih¹,Chang Chih-Hung²,Chan Yu-Wei³,Tasi Yin-Te²,Chu William C.⁴

Affiliation:

1. Providence University,Dept. of Computer Science and Information Engineering,Taichung,Taiwan

2. Providence University,Dept. of Computer Science and Communication Engineering,Taichung,Taiwan

3. Providence University,Dept. of Computer Science,Taichung,Taiwan

4. Tunghai University,Dept. of Computer Science,Taichung,Taiwan

Funder

Ministry of Science and Technology, Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9842455/9842394/09842588.pdf?arnumber=9842588

Reference11 articles.

1. OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields

2. Long Short-Term Memory

3. Toward safe separation distance monitoring from rgb-d sensors in human-robot interaction;svarny;International PhD Conference on Safe and Social Robotics (SSR2018),2018

4. Very deep convolutional networks for large-scale image recognition;simonyan;CoRR abs/1409 I556,2014

5. Human fall detection on embedded platform using depth maps and wireless accelerometer

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