Computer vision for increasing safety in container handling operations

Abstract

Workers in ports work with and in close proximity of heavy machinery. Quay cranes used for moving containers between ships and the dockside yard are one of the most accident-prone equipment types. For picking up containers, these cranes are equipped with spreaders, i.e. lifting devices which are lowered down on top of containers and lock on to them mechanically. We are concerned here with monitoring a moving quay crane spreader so as to make sure that safe clearance distances are maintained from the locations of dock workers in a port container cargo handling environment. The paper describes the application of computer vision techniques to develop a model-based, monocular spreader tracker. By tracking in three dimensions the position and orientation of the spreader during loading and unloading operations, a threat volume enclosing it can be defined. Constantly monitoring the distance of dock workers from this threat volume can improve the operator’s situational awareness and increase safety in the work environment. Quantitative experimental evaluation is also reported.