Real-time fall detection algorithm based on FFD-AlphaPose and CTR–GCN

With the increasing prevalence of an aging population, falls present a substantial risk to the health of older adults, making fall detection and prevention a primary societal concern. In response to the challenges of inadequate real-time performance and low accuracy in existing methods, this paper p...

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Veröffentlicht in:	Journal of real-time image processing Jg. 22; H. 3; S. 109
Hauptverfasser:	Yang, Xuecun, Wang, Yixiang, Dong, Zhonghua, Li, Jiayu, Zhang, Qingyun, Qiang, Shushan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2025 Springer Nature B.V
Schlagworte:	Accuracy Adaptability Algorithms Artificial neural networks Computer Graphics Computer Science Fall detection False alarms Frames per second Human body Image Processing and Computer Vision Methods Multilayers Multimedia Information Systems Neural networks Object recognition Older people Parameters Pattern Recognition Pose estimation Real time Signal,Image and Speech Processing Single persons Topology FFD-YOLO AlphaPose C2fPDR Fall detection
ISSN:	1861-8200, 1861-8219
Online-Zugang:	Volltext
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