Vision-Based Tower Crane Tracking for Understanding Construction Activity

Abstract

Visual monitoring of construction worksites through the installation of surveillance cameras has become prevalent in the construction industry. These cameras also are useful for automatic observation of construction events and activities. This paper demonstrates the use of a surveillance camera for assessing tower crane activities during the course of a workday. In particular, it seeks to demonstrate that the crane jib trajectory, together with known information regarding the site plans, provides sufficient information to infer the activity states of the crane. The jib angle trajectory is tracked by using two-dimensional to three-dimensional rigid pose tracking algorithms. The site plan information includes a process model for the activities and site layout information. A probabilistic graph model for crane activity is designed to process the track signals and recognize crane activity as belonging to one of two categories: concrete pouring and nonconcrete material movement. The experimental results from a construction surveillance camera show that crane activities are correctly identified.