Image-based construction of building energy models using computer vision

GÜRSEL DİNO İ., Sari A. E., Iseri O. K., Akin S., Kalfaoglu E., Erdogan B., ...More

AUTOMATION IN CONSTRUCTION, vol.116, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 116
  • Publication Date: 2020
  • Doi Number: 10.1016/j.autcon.2020.103231
  • Journal Name: AUTOMATION IN CONSTRUCTION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Communication Abstracts, Compendex, ICONDA Bibliographic, INSPEC, Metadex, Civil Engineering Abstracts
  • Keywords: 3D modeling, Building energy modeling, Computer vision, 3D reconstruction, Infrared imaging, INFRARED THERMOGRAPHY, EXISTING BUILDINGS, POINT CLOUDS, PERFORMANCE ASSESSMENT, U-VALUE, BIM, FUSION, SYSTEM, RECONSTRUCTION, SEGMENTATION
  • Middle East Technical University Affiliated: Yes

Abstract

Improving existing buildings' energy performance requires energy models that accurately represent the building. Computer vision methods, particularly image-based 3D reconstruction, can effectively support the creation of 3D building models. In this paper, we present an image-based 3D reconstruction pipeline that supports the semi-automated modeling of existing buildings. We developed two methods for the robust estimation of the building planes from a 3D point cloud that (i) independently estimate each plane and (ii) impose a perpendicularity constraint to plane estimation. We also estimate external walls' thermal transmittance values using an infrared thermography-based method, with the surface temperatures measured by a thermal camera. We validate our approach (i) by testing the pipeline's ability in constructing accurate surface models subject to different image sets with varying sizes and levels of image quality, and (ii) through a comparative analysis between the calculated energy performance metrics of a ground truth and calculated energy simulation model.