ABSTRACT
The monitoring of the construction progress is an essential task on construction sites, which nowadays is conducted mostly by hand. Recent image processing techniques provide a promising approach for reducing manual labor on site. While modern machine learning algorithms such as convolutional neural networks have proven to be of sublime value in other application fields, they are widely neglected by the CAE industry so far. In this paper, we propose a strategy to set up a machine learning routine to detect construction elements on UAV photographs of construction sites. In an accompanying case study using 750 photographs containing nearly 10.000 formwork elements, we reached accuracies of 90% when classifying single object images and 30% when locating formwork on multi-object images.
