Live demonstration: Vision-based real-time fall detection system on embedded system

Tsung Han Tsai; Chin Wei Hsu; Wei Chung Wan

Live demonstration: Vision-based real-time fall detection system on embedded system

Tsung Han Tsai
, Chin Wei Hsu
, Wei Chung Wan

電機工程學系

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

6 引文斯高帕斯（Scopus）

摘要

In this paper, we proposed an implementation of fall detection system on Raspberry Pi with the Intel® Neural Compute Stick 2. Firstly, we used skeleton extraction algorithm to obtain the important skeleton information. Secondly, we proposed a robustness neural network using pruning method to reduce the parameter and calculation and combined with the neural compute stick to execute the module. The final result will transfer to the Raspberry Pi to display on the monitor. As a result, it can be implemented on the smaller embedded system.

原文	???core.languages.en_GB???
主出版物標題	2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings
發行者	Institute of Electrical and Electronics Engineers Inc.
ISBN（電子）	9781728133201
出版狀態	已出版 - 2020
事件	52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Virtual, Online 持續時間: 10 10月 2020 → 21 10月 2020

出版系列

名字	Proceedings - IEEE International Symposium on Circuits and Systems
卷	2020-October
ISSN（列印）	0271-4310

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???event.eventtypes.event.conference???	52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020
城市	Virtual, Online
期間	10/10/20 → 21/10/20

引用此

Tsai, T. H., Hsu, C. W., & Wan, W. C. (2020). Live demonstration: Vision-based real-time fall detection system on embedded system. 於 2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings 文章 9181262 (Proceedings - IEEE International Symposium on Circuits and Systems; 卷 2020-October). Institute of Electrical and Electronics Engineers Inc..

@inproceedings{334cdf6568ac44aabc5735f4985606c0,

title = "Live demonstration: Vision-based real-time fall detection system on embedded system",

abstract = "In this paper, we proposed an implementation of fall detection system on Raspberry Pi with the Intel{\textregistered} Neural Compute Stick 2. Firstly, we used skeleton extraction algorithm to obtain the important skeleton information. Secondly, we proposed a robustness neural network using pruning method to reduce the parameter and calculation and combined with the neural compute stick to execute the module. The final result will transfer to the Raspberry Pi to display on the monitor. As a result, it can be implemented on the smaller embedded system.",

keywords = "CNN, Fall detection, Neural compute stick2, Raspberry pi",

author = "Tsai, \{Tsung Han\} and Hsu, \{Chin Wei\} and Wan, \{Wei Chung\}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020 ; Conference date: 10-10-2020 Through 21-10-2020",

year = "2020",

language = "???core.languages.en\_GB???",

series = "Proceedings - IEEE International Symposium on Circuits and Systems",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings",

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Tsai, TH, Hsu, CW & Wan, WC 2020, Live demonstration: Vision-based real-time fall detection system on embedded system. 於 2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings., 9181262, Proceedings - IEEE International Symposium on Circuits and Systems, 卷 2020-October, Institute of Electrical and Electronics Engineers Inc., 52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020, Virtual, Online, 10/10/20.

Live demonstration: Vision-based real-time fall detection system on embedded system. / Tsai, Tsung Han; Hsu, Chin Wei; Wan, Wei Chung.
2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. 9181262 (Proceedings - IEEE International Symposium on Circuits and Systems; 卷 2020-October).

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

TY - GEN

T1 - Live demonstration

T2 - 52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020

AU - Tsai, Tsung Han

AU - Hsu, Chin Wei

AU - Wan, Wei Chung

PY - 2020

Y1 - 2020

N2 - In this paper, we proposed an implementation of fall detection system on Raspberry Pi with the Intel® Neural Compute Stick 2. Firstly, we used skeleton extraction algorithm to obtain the important skeleton information. Secondly, we proposed a robustness neural network using pruning method to reduce the parameter and calculation and combined with the neural compute stick to execute the module. The final result will transfer to the Raspberry Pi to display on the monitor. As a result, it can be implemented on the smaller embedded system.

AB - In this paper, we proposed an implementation of fall detection system on Raspberry Pi with the Intel® Neural Compute Stick 2. Firstly, we used skeleton extraction algorithm to obtain the important skeleton information. Secondly, we proposed a robustness neural network using pruning method to reduce the parameter and calculation and combined with the neural compute stick to execute the module. The final result will transfer to the Raspberry Pi to display on the monitor. As a result, it can be implemented on the smaller embedded system.

KW - CNN

KW - Fall detection

KW - Neural compute stick2

KW - Raspberry pi

UR - https://www.scopus.com/pages/publications/85109303146

M3 - 會議論文篇章

AN - SCOPUS:85109303146

T3 - Proceedings - IEEE International Symposium on Circuits and Systems

BT - 2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 10 October 2020 through 21 October 2020

ER -

Live demonstration: Vision-based real-time fall detection system on embedded system

摘要

出版系列

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指紋

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