Skeleton-based human action evaluation using graph convolutional network for monitoring Alzheimer’s progression

•We propose a novel two-task graph convolutional network (2T-GCN) to represent skeleton data for human action evaluation (HAE) tasks of abnormality detection and quality evaluation. To the best of our knowledge, this is the first work that applies GCN to skeleton-based HAE.•We validate the effective...

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Veröffentlicht in:	Pattern recognition Jg. 119; S. 108095
Hauptverfasser:	Yu, Bruce X.B., Liu, Yan, Chan, Keith C.C., Yang, Qintai, Wang, Xiaoying
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.11.2021
Schlagworte:	Abnormality detection Alzheimer’s disease Graph neural network Human action evaluation Abnormality detection Human action evaluation Alzheimer’s disease Graph neural network
ISSN:	0031-3203, 1873-5142
Online-Zugang:	Volltext
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