VBuilt : Volume-based automatic building extraction for as-built point clouds

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Research units

  • Carnegie Mellon University


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.


Original languageEnglish
Title of host publicationAutomation and robotics in construction. International symposium
EditorsM. Al-Hussein
Publication statusPublished - 1 Jan 2019
MoE publication typeA4 Article in a conference publication
EventInternational Symposium on Automation and Robotics in Construction - Banff, Canada
Duration: 21 May 201924 May 2019
Conference number: 36


ConferenceInternational Symposium on Automation and Robotics in Construction
Abbreviated titleISARC

    Research areas

  • Building extraction, Convex hull, Crane cameras, Progress monitoring

ID: 40605043