A study of falling behavior recognition of the elderly based on deep learning

The current computer vision-based elderly falling behavior recognition algorithm mainly uses target detection followed by behavior recognition for a single human body, but there are mostly numerous human targets and noise interference in the actual scene, which makes it difficult to accurately detec...

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Bibliographic Details
Published in:	Signal, image and video processing Vol. 18; no. 10; pp. 7383 - 7394
Main Authors:	Xu, Pengfei, Sulaiman, Nor Anis Asma, Ding, Yafei, Zhao, Jiangwei, Li, Shengpu
Format:	Journal Article
Language:	English
Published:	London Springer London 01.09.2024 Springer Nature B.V
Subjects:	Accelerometers Aging Algorithms Artificial neural networks Behavior Computer Imaging Computer Science Computer vision Deep learning Falling Falls Gesture recognition Human body Human motion Image Processing and Computer Vision Machine learning Monitoring systems Multimedia Information Systems Older people Original Paper Pattern Recognition and Graphics Physiology Population Sensors Signal,Image and Speech Processing Target detection Time lag Tracking Vision Wearable computers Canada South Korea Australia United States > US China Japan Anomalous behavior Camshift algorithm ST-GCN algorithm HOG algorithm
ISSN:	1863-1703, 1863-1711
Online Access:	Get full text
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