Abstract
This paper offers a workflow for generating synthetic point cloud data sets to be used in deep learning algorithms in tasks of modeling historical architectural elements. Documentation of cultural heritage is a time-consuming process that requires high precision. Computational and semi-automatic tools enhance conventional methods to shorten the duration of the documentation phase and increase the accuracy of the output. Photogrammetry and laser scanning are how geometrical data is acquired and delivered as a point cloud with position, color, and optionally normal vector information. Segmenting architectural elements based on our interpretations of this data is possible using deep neural networks but is limited when, despite the millions of points from one building, the data is insufficient in terms of variance and quantity. To overcome this limitation, we propose a semi-automatic synthetic data set generation using parametric definitions of historic architectural elements. We create a synthetic dataset, namely the Historical Dome Dataset (HDD), consisting of nearly 1000 dome systems with four semantic classes. We quantitatively and qualitatively analyze the usefulness of the HDD by training a number of modern neural networks on it. Our method of synthesizing point clouds can quickly be adapted into similar cultural heritage projects to prepare relevant data to accurately train deep neural networks and process the collected cultural heritage data.
Original language | English |
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Title of host publication | Computer-Aided Architectural Design. Design Imperatives |
Subtitle of host publication | The Future is Now - 19th International Conference, CAAD Futures 2021, Selected Papers |
Editors | David Gerber, Evangelos Pantazis, Biayna Bogosian, Alicia Nahmad, Constantinos Miltiadis |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 538-554 |
Number of pages | 17 |
ISBN (Print) | 9789811912795 |
DOIs | |
Publication status | Published - 2022 |
Event | 19th International Conference on Computer-Aided Architectural Design Futures, CAAD Futures 2021 - Virtual, Online Duration: 16 Jul 2021 → 18 Jul 2021 |
Publication series
Name | Communications in Computer and Information Science |
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Volume | 1465 CCIS |
ISSN (Print) | 1865-0929 |
ISSN (Electronic) | 1865-0937 |
Conference
Conference | 19th International Conference on Computer-Aided Architectural Design Futures, CAAD Futures 2021 |
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City | Virtual, Online |
Period | 16/07/21 → 18/07/21 |
Bibliographical note
Publisher Copyright:© 2022, Springer Nature Singapore Pte Ltd.
Funding
Acknowledgements. This work is supported by TÜB˙TAK (The Scientific and Technological Research Council of Turkey) Project Number: 119K896. A very special thanks to Demircan Tas¸ and Berkay Öztürk for providing photogrammetric data. Lastly, we would like to thank our research group for their valuable discussions.
Funders | Funder number |
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TÜB˙TAK | |
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu | 119K896 |
Keywords
- Cultural heritage
- Deep learning
- Point clouds
- Synthetic data set
- Training data