Human skeleton pose and spatio-temporal feature-based activity recognition using ST-GCN

Skeleton-based Human Activity Recognition has recently sparked a lot of attention because skeleton data has proven resistant to changes in lighting, body sizes, dynamic camera perspectives, and complicated backgrounds. The Spatial-Temporal Graph Convolutional Networks (ST-GCN) model has been exposed...

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Bibliographic Details
Published in:	Multimedia tools and applications Vol. 83; no. 5; pp. 12705 - 12730
Main Authors:	Lovanshi, Mayank, Tiwari, Vivek
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.02.2024 Springer Nature B.V
Subjects:	Algorithms Artificial neural networks Comparative studies Computer Communication Networks Computer Science Data Structures and Information Theory Datasets Deep learning Feature recognition Human activity recognition Human body Human mechanics Human motion Information technology Kinetics Model accuracy Multimedia Multimedia Information Systems Neural networks Pose estimation Sentiment analysis Smart houses Special Purpose and Application-Based Systems Surveillance Topology Activity recognition ST-GCN Skeleton joints Spatio-temporal feature Pose estimation
ISSN:	1573-7721, 1380-7501, 1573-7721
Online Access:	Get full text
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