| id |
caadria2023_161 |
| authors |
Zhao, Mingming, Ding, Cao and Crossley, Tatjana |
| year |
2023 |
| title |
Integration of EEG and Deep Learning on Design Decision-Making: A Data-Driven Study of Perception in Immersive Virtual Architectural Environments |
| doi |
https://doi.org/10.52842/conf.caadria.2023.1.089
|
| source |
Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 89–98 |
| summary |
Immersive virtual reality(IVR) as an emerging architectural design tool is utilized by many architecture firms to assist in better design decision-making. It allows users to immersively experience the simulated architectural environment prior to real construction. However, compared to conventional computational design tools, IVR faces more challenges in assessing the perception of designed simulations and visualizations. This paper attempts to examine the possibilities for incorporating human biological data and deep learning technology into the process of immersive visualization in architectural design. It aims to objectively understand human perception in an immersive virtual architectural environment, and ultimately assist in design decision-making and human-centered architectural design. The study proposes a novel and multidisciplinary use of techniques derived from psychology, computer science, and architecture disciplines to explore how biological data might be understood architecturally and vice versa. It also provides an opportunity to explore ways of using IVR-based computational design in the new metaverse era. The experiment results illustrate that there is a significant correlation between environmental experience and brain activation. It indicates the integration of EEG and deep learning is helpful to perform as complementary tools for better understanding human perception in immersive virtual architectural environments. |
| keywords |
Architectural Design Decision-Making, Eye Tracking, Electroencephalogram(EEG), Convolutional Neural Networks(CNN), Virtual Reality(VR) |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (1,348,778 bytes) |
| references |
Content-type: text/plain
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| last changed |
2023/06/15 23:14 |
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