Analysis of masonry work activity recognition accuracy using a spatiotemporal graph convolutional network across different camera angles

Human activity recognition (HAR) in construction has gained attention for its potential to improve safety and productivity. While HAR research has shifted toward vision-based approaches, many studies typically use data from a specific angle, limiting understanding of how camera angles affect accurac...

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Veröffentlicht in:	Automation in construction Jg. 175; S. 106178
Hauptverfasser:	Yun, Sangyoon, Hong, Sungkook, Hwang, Sungjoo, Lee, Dongmin, Kim, Hyunsoo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.07.2025
Schlagworte:	AlphaPose Camera angle Human Activity Recognition (HAR) Spatial-Temporal Graph Convolutional Network (ST-GCN) Human Activity Recognition (HAR) AlphaPose Camera angle Spatial-Temporal Graph Convolutional Network (ST-GCN)
ISSN:	0926-5805
Online-Zugang:	Volltext
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