Construction progress monitoring is an essential but time-consuming work on all construction sites. This research introduces a method to facilitate the asplanned versus as-built comparison through image based monitoring. A dense point cloud is reconstructed from the images that is compared to an existing 4D building information model (BIM). However, due to the numerous obstructions found on a construction site, only a minority of building elements can be detected directly. In this paper, we discuss how the detection results are significantly refined and enriched by using additional spatial and temporal information gained from the 4D BIM. In this regard, a precedence relationship graph is derived which helps to identify occluded elements and enhance the detection algorithm.
A dense point cloud was reconstructed from the images that is compared to an existing 4D building information model (BIM) REF .
Automated Progress Monitoring Based on Photogrammetric Point Clouds and Precedence Relationship Graphs
Proceedings of the 32nd International Symposium on Automation and Robotics in Construction and Mining (ISARC 2015)
Proceedings of the 32nd International Symposium on Automation and Robotics in Construction and Mining (ISARC 2015)
Engineering