Deep Learning Spatial Signature Inverted GANs for isovist representation in architectural floorplan

Mikhael Johanes, Jeffrey Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The advances of Generative Adversarial Networks (GANs) have provided a new experimental ground for creative architecture processes. However, the analytical potential ofthe latent representation of GANs is yet to be exploredfor architectural spatial analysis. Furthermore, most research on GANs for floorplan learning in architecture uses images as its main representation medium. This paper presents an experimental framework that uses one-dimensional periodic isovist samples and GANs inversion to recover its latent representation. Access to GANs’ latent space will open up a possibility for discriminative tasks such as classification and clustering analysis. The resulting latent representation will be investigated to discover its analytical capacity in extracting isovist spatial patterns from thousands of floorplans data. In this experiment, we hypothetically conclude that the spatial signature of the architectural floor plan could be derived from the degree of regularity of isovist samples in the latent space structure. The finding of this research will enable a new data-driven strategy to measure spatial quality using isovist and provide a new way for indexing architectural floorplan.

Original languageEnglish
Title of host publicationeCAADe 2022 - Co-creating the Future
Subtitle of host publicationInclusion in and through Design
EditorsBurak Pak, Gabriel Wurzer, Rudi Stouffs
PublisherEducation and research in Computer Aided Architectural Design in Europe
Pages621-629
Number of pages9
ISBN (Print)9789491207334
Publication statusPublished - 2022
Event40th Conference on Education and Research in Computer Aided Architectural Design in Europe, eCAADe 2022 - Ghent, Belgium
Duration: 13 Sep 202216 Sep 2022

Publication series

NameProceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe
Volume2
ISSN (Print)2684-1843

Conference

Conference40th Conference on Education and Research in Computer Aided Architectural Design in Europe, eCAADe 2022
Country/TerritoryBelgium
CityGhent
Period13/09/2216/09/22

Keywords

  • GANs Inversion
  • Isovist
  • Latent Representation
  • Machine Learning
  • Signature
  • Spatial

Fingerprint

Dive into the research topics of 'Deep Learning Spatial Signature Inverted GANs for isovist representation in architectural floorplan'. Together they form a unique fingerprint.

Cite this