A real-time fall detection model based on BlazePose and improved ST-GCN

Providing timely rescue when a fall occurs can greatly reduce fall mortality for older people. With the growing number of single-resided elders, real-time smart fall incident detection has become a new research hotspot. Accuracy, computational complexity and real-time response are key issues to be s...

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Veröffentlicht in:	Journal of real-time image processing Jg. 20; H. 6; S. 121
Hauptverfasser:	Zhang, Yu, Gan, Junsi, Zhao, Zewei, Chen, Junliang, Chen, Xiaofeng, Diao, Yinliang, Tu, Shuqin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2023 Springer Nature B.V
Schlagworte:	Accuracy Algorithms Artificial neural networks Computer Graphics Computer Science Edge computing Fall detection Human body Image Processing and Computer Vision Model accuracy Multimedia Information Systems Pattern Recognition Real time Semantics Signal,Image and Speech Processing Target recognition Time response Real-time fall detection Pose estimation Improved spatial–temporal graph convolution Edge computing
ISSN:	1861-8200, 1861-8219
Online-Zugang:	Volltext
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