With the spread of camera-equipped devices, massive images and videos are recorded on construction sites daily, and the ever-increasing volume of digital images has inspired scholars to visually capture the actual status of construction sites from them. Three-dimensional (3D) reconstruction is the key to connecting the Building Information Model and the project schedule to daily construction images, which enables managers to compare as-planned with as-built status and detect deviations and therefore monitor project progress. Many scholars have carried out extensive research and produced a variety of intricate methods. However, few studies comprehensively summarize the existing technologies and introduce the homogeneity and differences of these technologies. Researchers cannot clearly identify the relationship between various methods to solve the difficulties. Therefore, this paper focuses on the general technical path of various methods and sorts out a comprehensive research map, to provide reference for researchers in the selection of research methods and paths. This is followed by identifying gaps in knowledge and highlighting future research directions. Finally, key findings are summarized.

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Monitoring construction progress is essential for project management. A variety of excellent automatic schedule acquisition methods have been proposed, particularly 3D reconstruction. However, both laser-based and image-based 3D reconstruction methods rely on point clouds which have some inherent defects. In this study, a rough registration method was proposed to obtain construction progress. The method does not generate point clouds during the entire process but determines the actual construction progress by registering the target detection results and the projection of building information model elements. The method was tested at the construction sites of commercial and residential buildings. The experimental results indicated that the registration accuracy reached 95.13%. The average external parameter calibration time and the registration time of each image are 18.57s and 50.59ms, respectively. Compared to similar 3D reconstruction methods, the proposed method is realistic, fast, and simple. This provides a promising method for 3D reconstruction from unordered construction-site images.

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