Image-based construction of building energy models using computer vision

Date

2020-08-01

Author

Gürsel Dino, İpek
Iseri, Orcun Koral
Akin, Sahin
Kalfaoglu, Esat
Erdogan, Bilge
Kalkan, Sinan
Alatan, Abdullah Aydın

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

Subject Keywords

Control and Systems Engineering, Civil and Structural Engineering, Building and Construction

URI

https://hdl.handle.net/11511/39539

Journal

AUTOMATION IN CONSTRUCTION

DOI

https://doi.org/10.1016/j.autcon.2020.103231

Collections

Department of Architecture, Article

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Citation Formats

İ. Gürsel Dino et al., “Image-based construction of building energy models using computer vision,” AUTOMATION IN CONSTRUCTION, pp. 0–0, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39539.