Monitoring the progress of a large construction site manually is a challenging task for managers. By collecting visual data of the site, many monitoring tasks can be automated using machine vision techniques. In this work, we study a new method of collecting site data, which is through crane camera images used to create 3D point clouds. The technology is cost-effective and enables automatic capturing and transmission of on-site data. To automatically extract buildings from the as-built point clouds, we present VBUILT, which uses 3D convex hull volumes to identify building clusters. Experimental results on 40 point clouds collected over four months on a large construction site show that the proposed algorithm can identify building clusters with 100% accuracy.