Model-Driven Visual Data Capture on Construction Sites: Method and Metrics of Success

Today, camera-equipped unmanned aerial vehicles (UAVs) are frequently used to capture large amount of images and videos on construction sites. Research has focused on methods that organize such data spatially and temporally, map them into 4D BIM, and use the resulting models for project monitoring applications. To guarantee quality in the data capturing process, this paper introduces a BIM-driven flight planning method. Specifically, a cloud-based 4D BIM environment is presented that highlights expected changes prior to capture. Based on a set of user-defined UAV waypoints that specify camera location and pose, a capture path is fit into the 4D BIM environment. The quality of the capture is then assessed per element using metrics of visibility (2D surface area associated with each element in each visual observation) and redundancy across visual observations. The effectiveness of the method and metrics are discussed using data from a pilot project.