AIJ Journal of Technology and Design
Online ISSN : 1881-8188
Print ISSN : 1341-9463
ISSN-L : 1341-9463
Information Systems Technology
FEATURE REPRESENTATION FOR FLOOR PLANS USING RANDOM VISIBILITY GRAPH AND GRAPH NEURAL NETWORK
Keita KADO
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2025 Volume 31 Issue 77 Pages 585-589

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Abstract

Floor plans are widely used for representing residential spaces. This study aims to propose a feature representation method for floor plans, namely unstructured image data, using a Random Visibility Graph and Graph Neural Network. In this method, the feature representation is performed using Invariant Information Clustering. To prepare a dataset, the Random Visibility Graph is designed to derive multiple graphs from a single floor plan effectively. The obtained features formed shape-oriented clusters, rather than ordinary variables such as area. In addition, the similarity of features corresponds to the similarity of plans, including slight differences in the connectivity of rooms.

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© 2025, Architectural Institute of Japan
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