VI-Net—View-Invariant Quality of Human Movement Assessment

We propose a view-invariant method towards the assessment of the quality of human movements which does not rely on skeleton data. Our end-to-end convolutional neural network consists of two stages, where at first a view-invariant trajectory descriptor for each body joint is generated from RGB images...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 20; H. 18; S. 5258
Hauptverfasser:	Sardari, Faegheh, Paiement, Adeline, Hannuna, Sion, Mirmehdi, Majid
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI 15.09.2020 MDPI AG
Schlagworte:	Artificial Intelligence Computer Science Computer Vision and Pattern Recognition health monitoring Humans Image Processing Machine Learning Movement movement analysis Neural and Evolutionary Computing Neural Networks, Computer Signal and Image Processing view-invariant convolutional neural network (CNN) health monitoring view-invariant convolutional neural network (CNN) movement analysis
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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