Improved and Visually Enhanced Case-Based Retrieval of Room Configurations for Assistance in Architectural Design Education

Viktor Eisenstadt, Christoph Langenhan, Klaus-Dieter Althoff, Andreas Dengel

In: Ian Watson , Rosina Weber (Hrsg.). Case-Based Reasoning Research and Development. International Conference on Case-Based Reasoning (ICCBR-2020) June 8-12 Salamance Spain Seiten 213-228 Springer 2020.


This paper presents a system for case-based retrieval of architectural designs in the form of graph-based room configurations by means of applying a case preselection process using a convolutional neural network and the subsequent graph and subgraph matching on the preselected cases. An integral part of the system is its specific user interface that visualizes the architectural concepts of the system in the way familiar for the target user group. The goal of the system is to support higher architectural education with digital assistance methods by providing a tool that can be used to enhance early design phases. The evaluation showed that the system outperforms its predecessor and is suitable for use in education. The approach was developed in context of a bigger framework, however, the research can be considered self-contained and the methods transferred to the domains other than architecture.

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iccbr2020_VE.pdf (pdf, 738 KB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence