Object Recognition in Construction-Site Images Using 3D CAD-Based Filtering

Abstract

Construction-site images that are now easily obtained from digital cameras have the potential to automatically provide the project status information. For example, once construction objects such as concrete columns are accurately identified and counted, the current level of project progress in the column installation activity can easily be measured. However, in order to identify and count the number of concrete columns installed at a particular point of time, a robust object recognition methodology is required. Without the successful recognition and extraction of the construction object of interest, it is almost impossible to understand the current level of project progress. This paper presents a robust image processing methodology to effectively extract the objects of interest from construction-site digital images. The proposed methodology makes use of advanced imaging algorithms and a three-dimensional computer aided design perspective view to increase the accuracy of the object recognition. Tests show that the methodology is promising and expected to provide a solid base for the successful, automatic acquisition of project information.