Publikation

Semantic Pattern-Based Retrieval of Architectural Floor Plans with Case-Based and Graph-Based Searching Techniques and their Evaluation and Visualization

Qamer Uddin Sabri, Johannes Bayer, Viktor Eisenstadt, Syed Saqib Bukhari, Klaus-Dieter Althoff, Andreas Dengel

In: Maria De Marsico, Gabriella Sanniti di Baja, Ana Fred (Hrsg.). Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods. International Conference on Pattern Recognition Applications and Methods (ICPRAM-2017) February 24-26 Porto Portugal Seiten 50-60 ISBN 978-989-758-222-6 Scitepress 2017.

Abstrakt

Until today, for the conceptual design of architectural floor plans, architects widely follow the traditional pen and paper based method to draw the conceptual floor plans, and retrieve the similar floor plans in the printed reference collections. In this paper we present a complete end-to-end system that helps architects to retrieve similar floor plans in early design phases. This work makes a three-fold contribution. Firstly, we have adapted three state of the art techniques to retrieve the similar floor plans: case-based reasoning (CBR), exact graph matching, and inexact graph matching. Secondly, we conducted a test to detect the computational limits of the searching techniques. And finally, we performed a qualitative analysis by running more realistic test cases created by architects while keeping in mind the computational limits. For visualization of results, we have integrated advanced version of our previously implemented web-based user interface. The qualitative analysis showed that the exact graph matching gives in general better results for a majority of test cases, as compared to other two methods. The novelty of our approach is that it combines CBR, exact, and inexact graph matching in one system in the domain of retrieval of architectural floor plans.

Weitere Links

54-Qamer-Floor-Plan-Searching-ICPRAM17.pdf (pdf, 963 KB)

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence