Synthetic data-driven framework for estimating worker activity intensity using pose-based graph neural networks
This paper proposes a metabolic equivalent of task (MET) class prediction framework that combines Stable Diffusion-generated synthetic images with B-ResSkelGCN, which learns from skeleton graphs, for non-contact evaluation of construction workers' workload levels. Using domain-informed prompts, synthetic images were ge...
Junhong Kim, Kieun Lee, Youngseo Hwang et al.
· Automation in Construction · 0 citations