| id |
caadria2024_369 |
| authors |
Katsangelou, Smaro, Wilmoth, Parker, Pados, Dimitris A. and Vermisso, Emmanouil |
| year |
2024 |
| title |
Latent Petroglyphs: Pattern Extraction From Prehistoric Rock Art Through Generative Workflows for a Design Project in Greece |
| doi |
https://doi.org/10.52842/conf.caadria.2024.1.149
|
| source |
Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 1, pp. 149–158 |
| summary |
This paper regards the translation of indigenous rock art (petroglyphs) into training data for deep learning algorithms. Vis-a-vis the recent popularity of pre-trained AI models, the authors examine the potential of domain-specific search procedures to inform the process for a building design in Greece. Petroglyphs are a primitive form of artistic expression which has survived through the ages due to the medium upon which it was engraved. The practical aspect of this art was navigating through nature. The “Rock Art Center” aims to exhibit the narratives and culture behind rock art scattered in the mountains. Considering the adoption of generative adversarial networks (GANs) in the architectural workflow, the landscape and local prehistoric graffiti are viewed as datasets for tackling different design decisions, formally and conceptually interrogating the project’s scope. The existing rock art sites serve as the primary dataset to explore the building’s form, by accessing the 'latent' space of prehistoric rock art and its interpolation with the demands of the project. A number of algorithms and digital tools is employed to interpret the data in question. |
| keywords |
Artificial Intelligence, Deep Learning, Architectural Ideation, Design Workflow, Image Generation |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (1,978,187 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/11/17 22:05 |
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