SKIP: Accurate Fall Detection Based on Skeleton Keypoint Association and Critical Feature Perception-Reference-Cited by-同舟云学术

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SKIP: Accurate Fall Detection Based on Skeleton Keypoint Association and Critical Feature Perception

Published:2024-05-01 Issue:9 Volume:24 Page:14812-14824
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Du Chenjie¹^ORCID,Jin Ran¹,Tang Hao²^ORCID,Jiang Qiuping³^ORCID,He Zhiwei⁴^ORCID

Affiliation:

1. College of Big Data and Software Engineering, Zhejiang Wanli University, Ningbo, China

2. Department of Information Technology and Electrical Engineering, ETH Zürich, Zürich, Switzerland

3. Faculty of Information Science and Engineering, Ningbo University, Ningbo, China

4. Faculty of Electronics Information, Hangzhou Dianzi University, Hangzhou, China

Funder

Natural Science Foundation of China

Key Research and Development Program of Zhejiang Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10516472/10478855.pdf?arnumber=10478855

Reference54 articles.

1. Human activity recognition using machine learning methods in a smart healthcare environment

2. Semantic-based technologies for video analysis in activity recognition, video surveillance and smart home domains

3. Unobtrusive Human Fall Detection System Using mmWave Radar and Data Driven Methods

4. Multimodal spatiotemporal skeletal kinematic gait feature fusion for vision-based fall detection;Amsaprabhaa;Expert Syst. Appl.,2023

5. A ubiquitous wheelchair fall detection system using low-cost embedded inertial sensors and unsupervised one-class SVM

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1. Towards intelligent environments: human sensing through 3D point cloud;Journal of Reliable Intelligent Environments;2024-08-06

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