Generative AI for Immersive Experiences: Integrating Text-to-Image Models in VR-Mediated Co-design Workflows

Book chapter


Bussell, C., Ahmed, E., Hartle-Ryan, D. and Kapsalis, T. 2023. Generative AI for Immersive Experiences: Integrating Text-to-Image Models in VR-Mediated Co-design Workflows. in: Stephanidis, C., Antona, M., Ntoa, S. and Salvendy, G. (ed.) HCI International 2023 Posters: Book Subtitle 25th International Conference on Human-Computer Interaction, HCII 2023, Copenhagen, Denmark, July 23–28, 2023, Proceedings, Part V New York Springer. pp. 380–388
AuthorsBussell, C., Ahmed, E., Hartle-Ryan, D. and Kapsalis, T.
EditorsStephanidis, C., Antona, M., Ntoa, S. and Salvendy, G.
Abstract

Text-to-image AI models can generate novel images for design inspiration. Yet, their applications for collaborative design (co-design) purposes and interoperability within simulation-based, immersive settings have been scarcely explored. In this paper, we propose a novel, multi-modal approach for interactive public participation in urban design projects. The main objectives of our research are (a) to describe a methodological workflow of integrating text-to-image AI models into VR-mediated co-design workshops, and (b) to investigate the applicability of the proposed workflow through a set of completed and prospective case studies. Both studies are parts of a broader research project, which aims to revitalize the city of Derby, UK through producing a series of sustainable design visions. Through these case studies, we discuss some preliminary results and introduce our future work.

KeywordsText-to-image AI models; design inspiration ; urban design ; sustainable design
Page range380–388
Year2023
Book titleHCI International 2023 Posters: Book Subtitle 25th International Conference on Human-Computer Interaction, HCII 2023, Copenhagen, Denmark, July 23–28, 2023, Proceedings, Part V
PublisherSpringer
Place of publicationNew York
SeriesCommunications in Computer and Information Science
ISBN9783031360039
9783031360046
ISSN1865-0937
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-031-36004-6_52
Web address (URL)https://link.springer.com/chapter/10.1007/978-3-031-36004-6_52
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Output statusPublished
Publication dates
Online09 Jul 2023
Publication process dates
Deposited26 Jul 2023
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