Human Action Recognition of Spatiotemporal Parameters for Skeleton Sequences Using MTLN Feature Learning Framework

Human action recognition (HAR) by skeleton data is considered a potential research aspect in computer vision. Three-dimensional HAR with skeleton data has been used commonly because of its effective and efficient results. Several models have been developed for learning spatiotemporal parameters from...

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Autores principales:	Faisal Mehmood, Enqing Chen, Muhammad Azeem Akbar, Abeer Abdulaziz Alsanad
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	human action recognition (HAR) skeleton data spatiotemporal multi-task learning network (MTLN) convolutional neural network (CNN) Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/ef9865d76f654905b711d50b6b7c2dd9
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Human Action Recognition of Spatiotemporal Parameters for Skeleton Sequences Using MTLN Feature Learning Framework

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