Computer-vision based rapid entire body analysis (REBA) estimation




Construction safety, Computer vision, Ergonomic risks assessment, Machine learning, REBA


Although much attention has been paid to the safety risk of construction sites and ergonomic risk assessment of workers, the automation of ergonomic risk assessment has not been significantly developed. This article presents a non-intrusive, automated ergonomic risk assessment approach based on computer vision, machine learning, and Rapid Entire Body Assessment (REBA). The method is called Computer-Vison Based Rapid Entire Body Analysis Estimation (CVRE). This approach is expected to realize automated monitoring and early-stage warning of ergonomic risks by automating the procedure of calculating REBA scores for construction site workers. This method consists of machine learning-based key joints and joint angles estimation of human bodies and computer-vision-based automated risk estimation. With the extensive development of machine learning and computer vision, researchers have been paying attention to assessing ergonomic risks with machine learning techniques. The proposed method has been further validated using the experimental data obtained by a motion capture system.