Ontology-Based Semantic Construction Image Interpretation

Abstract

Image-based techniques have become integral to the construction sector, aiding in project planning, progress monitoring, quality control, and documentation. In this paper, we address two key challenges that limit our ability to fully exploit the potential of images. The first is the “semantic gap” between low-level image features and high-level semantic descriptions. The second is the lack of principled integration between images and other digital systems used in construction, such as construction schedules and building information modeling (BIM). These challenges make it difficult to effectively incorporate images into digital twins of construction (DTC), a critical concept that addresses the construction industry’s need for more efficient project management and decision-making. To address these challenges, we first propose an ontology-based construction image interpretation (CII) framework to formalize the interpretation and integration workflow. Then, the DiCon-SII ontology is developed to provide a formalized vocabulary for visual construction contents and features. DiCon-SII also acts as a bridge between images and other digital systems to help construct an image-involved DTC. To evaluate the practical application of DiCon-SII and CII in supporting construction management tasks and as a precursor to DTC, we conducted a case study involving drywall installation. Via this case study, we demonstrate how the proposed methods can be used to infer the operational stage of a construction process, estimate labor productivity, and retrieve specific images based on user queries.