Human action detection and ergonomic risk assessment at construction sites, by use of machine vision and deep learning

Abstract: The work described herein focuses on the real-time detection and pose analysis of human activities at construction sites, as well as on the evaluation of the ergonomics of these activities. The pose detection and ergonomic analysis utilize machine vision (MV) and deep learning technologies for the processing of images and/or video streams, and a “skeletonization” mechanism that upon detection of a human pose, measures the geometric properties of the pose’s keypoints in the skeletal shape and then calculates the corresponding scores according to the Rapid Entire Body Assessment (REBA) methodology.