TY - GEN
T1 - Towards the Integration of Image-Based Appearance Information into BIM
AU - Mengiste, Eyob
AU - García De Soto, Borja
AU - Hartmann, Timo
N1 - Publisher Copyright:
© 2021 Computing in Civil Engineering 2021 - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2021. All rights reserved.
PY - 2021
Y1 - 2021
N2 - We propose a method to improve the understanding and visualization of the actual condition of a construction site by automatically developing an as-is BIM using site-appearance information from images and the as-planned BIM model. This is achieved by generating point clouds (PCs) from site images applying structure from motion (SfM). The corresponding elements between PCs and the 3D BIM were automatically determined using geometric and position assets to register PCs into the as-planned BIM accurately. Moreover, material condition classification can be done using information from the point cloud data. This way, the as-is BIM can be enriched with additional information such as the actual material conditions. The proposed method has been demonstrated using a construction environment where the as-is BIM was developed automatically from a set of 130 site images and the as-planned BIM. The as-is model has been used to identify deviations between as-planned and as-is conditions.
AB - We propose a method to improve the understanding and visualization of the actual condition of a construction site by automatically developing an as-is BIM using site-appearance information from images and the as-planned BIM model. This is achieved by generating point clouds (PCs) from site images applying structure from motion (SfM). The corresponding elements between PCs and the 3D BIM were automatically determined using geometric and position assets to register PCs into the as-planned BIM accurately. Moreover, material condition classification can be done using information from the point cloud data. This way, the as-is BIM can be enriched with additional information such as the actual material conditions. The proposed method has been demonstrated using a construction environment where the as-is BIM was developed automatically from a set of 130 site images and the as-planned BIM. The as-is model has been used to identify deviations between as-planned and as-is conditions.
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U2 - 10.1061/9780784483893.054
DO - 10.1061/9780784483893.054
M3 - Conference contribution
AN - SCOPUS:85132568113
T3 - Computing in Civil Engineering 2021 - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2021
SP - 433
EP - 440
BT - Computing in Civil Engineering 2021 - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2021
A2 - Issa, R. Raymond A.
PB - American Society of Civil Engineers (ASCE)
T2 - 2021 International Conference on Computing in Civil Engineering, I3CE 2021
Y2 - 12 September 2021 through 14 September 2021
ER -