| Title |
A Development of Facade Dataset Construction Technology Using Deep Learning-based Automatic Image Labeling |
| Authors |
Gu, Hyeong-Mo ; Seo, Ji-Hyo ; Choo, Seung-Yeon |
| DOI |
https://doi.org/10.5659/JAIK_PD.2019.35.12.43 |
| Keywords |
Construction Dataset; Construction Database; Deep Learning; Facade; Automatic Image Labeling |
| Abstract |
The construction industry has made great strides in the past decades by utilizing computer programs including CAD. However, compared to
other manufacturing sectors, labor productivity is low due to the high proportion of workers' knowledge-based task in addition to simple
repetitive task. Therefore, the knowledge-based task efficiency of workers should be improved by recognizing the visual information of
computers. A computer needs a lot of training data, such as the ImageNet project, to recognize visual information. This study, aim at
proposing building facade datasets that is efficiently constructed by quickly collecting building facade data through portal site road view and
automatically labeling using deep learning as part of construction of image dataset for visual recognition construction by the computer. As a
method proposed in this study, we constructed a dataset for a part of Dongseong-ro, Daegu Metropolitan City and analyzed the utility and
reliability of the dataset. Through this, it was confirmed that the computer could extract the significant facade information of the portal site
road view by recognizing the visual information of the building facade image. Additionally, In contribution to verifying the feasibility of
building construction image datasets. this study suggests the possibility of securing quantitative and qualitative facade design knowledge by
extracting the facade design knowledge from any facade all over the world. |