Cooperative Fall Detection with Multiple Cameras

Jian Chiuan Hou; Wei Ming Xu; Yu Cheng Chu; Chih Lin Hu; Ying Hong Chen; Shi Chen; Lin Hui

doi:10.1109/ICCE-Taiwan55306.2022.9869279

Cooperative Fall Detection with Multiple Cameras

Jian Chiuan Hou, Wei Ming Xu, Yu Cheng Chu, Chih Lin Hu, Ying Hong Chen, Shi Chen, Lin Hui

Department of Communication Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

We propose a fall detection mechanism based on multi-camera cooperation in home space. Cameras capture image-based falling events, and self-organize a group using deep reinforcement learning. Neighbor cameras exchange sensing data and statuses in local network proximity. With information sharing in a group, cameras can improve the accuracy of decision making on falling events and cope with the limited fields of view against physical deployment of cameras in residential areas.

Original language	English
Title of host publication	Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	543-544
Number of pages	2
ISBN (Electronic)	9781665470506
DOIs	https://doi.org/10.1109/ICCE-Taiwan55306.2022.9869279
State	Published - 2022
Event	2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 - Taipei, Taiwan Duration: 6 Jul 2022 → 8 Jul 2022

Publication series

Name	Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

Conference

Conference	2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
Country/Territory	Taiwan
City	Taipei
Period	6/07/22 → 8/07/22

Keywords

cooperative computing
Fall detection
health care
image recognition
smart home

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ICCE-Taiwan55306.2022.9869279

Cite this

Hou, J. C., Xu, W. M., Chu, Y. C., Hu, C. L., Chen, Y. H., Chen, S., & Hui, L. (2022). Cooperative Fall Detection with Multiple Cameras. In Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 (pp. 543-544). (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-Taiwan55306.2022.9869279

Hou, Jian Chiuan ; Xu, Wei Ming ; Chu, Yu Cheng et al. / Cooperative Fall Detection with Multiple Cameras. Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 543-544 (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022).

@inproceedings{1297043653464bf2abf12b2e7f9f8fe9,

title = "Cooperative Fall Detection with Multiple Cameras",

abstract = "We propose a fall detection mechanism based on multi-camera cooperation in home space. Cameras capture image-based falling events, and self-organize a group using deep reinforcement learning. Neighbor cameras exchange sensing data and statuses in local network proximity. With information sharing in a group, cameras can improve the accuracy of decision making on falling events and cope with the limited fields of view against physical deployment of cameras in residential areas.",

keywords = "cooperative computing, Fall detection, health care, image recognition, smart home",

author = "Hou, {Jian Chiuan} and Xu, {Wei Ming} and Chu, {Yu Cheng} and Hu, {Chih Lin} and Chen, {Ying Hong} and Shi Chen and Lin Hui",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 ; Conference date: 06-07-2022 Through 08-07-2022",

year = "2022",

doi = "10.1109/ICCE-Taiwan55306.2022.9869279",

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series = "Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022",

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

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booktitle = "Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022",

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Hou, JC, Xu, WM, Chu, YC, Hu, CL, Chen, YH, Chen, S & Hui, L 2022, Cooperative Fall Detection with Multiple Cameras. in Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022, Institute of Electrical and Electronics Engineers Inc., pp. 543-544, 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022, Taipei, Taiwan, 6/07/22. https://doi.org/10.1109/ICCE-Taiwan55306.2022.9869279

Cooperative Fall Detection with Multiple Cameras. / Hou, Jian Chiuan; Xu, Wei Ming; Chu, Yu Cheng et al.
Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 543-544 (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Cooperative Fall Detection with Multiple Cameras

AU - Hou, Jian Chiuan

AU - Xu, Wei Ming

AU - Chu, Yu Cheng

AU - Hu, Chih Lin

AU - Chen, Ying Hong

AU - Chen, Shi

AU - Hui, Lin

PY - 2022

Y1 - 2022

N2 - We propose a fall detection mechanism based on multi-camera cooperation in home space. Cameras capture image-based falling events, and self-organize a group using deep reinforcement learning. Neighbor cameras exchange sensing data and statuses in local network proximity. With information sharing in a group, cameras can improve the accuracy of decision making on falling events and cope with the limited fields of view against physical deployment of cameras in residential areas.

AB - We propose a fall detection mechanism based on multi-camera cooperation in home space. Cameras capture image-based falling events, and self-organize a group using deep reinforcement learning. Neighbor cameras exchange sensing data and statuses in local network proximity. With information sharing in a group, cameras can improve the accuracy of decision making on falling events and cope with the limited fields of view against physical deployment of cameras in residential areas.

KW - cooperative computing

KW - Fall detection

KW - health care

KW - image recognition

KW - smart home

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U2 - 10.1109/ICCE-Taiwan55306.2022.9869279

DO - 10.1109/ICCE-Taiwan55306.2022.9869279

M3 - 會議論文篇章

AN - SCOPUS:85138748012

T3 - Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

SP - 543

EP - 544

BT - Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

Y2 - 6 July 2022 through 8 July 2022

ER -

Hou JC, Xu WM, Chu YC, Hu CL, Chen YH, Chen S et al. Cooperative Fall Detection with Multiple Cameras. In Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 543-544. (Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022). doi: 10.1109/ICCE-Taiwan55306.2022.9869279

Cooperative Fall Detection with Multiple Cameras

Abstract

Publication series

Conference

Keywords

UN SDGs

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