Geometry- and Appearance-based Reasoning of Construction Progress Monitoring

Kevin Han, Joseph DeGol, Mani Golparvar-Fard

Abstract: Although adherence to project schedules and budgets is most highly valued by project owners, more than 53% of typical construction projects are behind schedule and more than 66% suffer from cost overruns, partly due to inability to accurately capture construction progress. To address these challenges, this paper presents new geometry- and appearance-based reasoning methods for detecting construction progress, which has the potential to provide more frequent progress measures using visual data that are already being collected by general contractors. The initial step of geometry-based filtering detects the state of construction of Building Information Modeling (BIM) elements (e.g. in-progress, completed). The next step of appearance-based reasoning captures operation-level activities by recognizing different material types. Two methods have been investigated for the latter step: a texture-based reasoning for image-based 3D point clouds and color-based reasoning for laser scanned point clouds. This paper presents two case studies for each reasoning approach for validating the proposed methods. The results demonstrate the effectiveness and practical significances of the proposed methods.