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Development of Structure-Specific Architectural BIM Object Automatic Generation Technology for Reverse Design Based on Deep Learning
- Kim, Taehoon;
- Kim, Geunjae;
- Hong, Soonmin;
- Choo, Seungyeon
SCOPUS
0초록
This research developed a technology for classifying architectural objects based on point cloud data and creating Building Information Modeling (BIM) models in the reverse engineering process. This research analyzed the limitations in the process and current advancements in point cloud-based object recognition and classification technology, leveraging semantic segmentation. The classification method employed a semantic segmentation-based network to classify objects into desired classes within 3D point cloud data. Specifically, the TD3D network, known for its superior performance, was utilized in this study, with publicly available datasets used for training. Moreover, the developed algorithm for creating architectural object BIM models was specifically designed based on the simplest structure and form, namely reinforced concrete structure. In conclusion, the study aimed to develop technology more aligned with the fundamental purpose of performing reverse engineering in an architectural context. Analysis of validated architectural structures revealed that, despite deviating from actual measurement times, concrete-reinforced structures demonstrated the highest performance. © 2024, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.
키워드
- 제목
- Development of Structure-Specific Architectural BIM Object Automatic Generation Technology for Reverse Design Based on Deep Learning
- 저자
- Kim, Taehoon; Kim, Geunjae; Hong, Soonmin; Choo, Seungyeon
- 발행일
- 2024
- 유형
- Conference paper
- 저널명
- Proceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe
- 권
- 1
- 페이지
- 705 ~ 714
- 언어
- ENG
- 출판사
- Education and research in Computer Aided Architectural Design in Europe
- 분량
- 10 페이지
- ISSN
- P 2684-1843