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Article

Framework for Indoor Elements Classification via Inductive Learning on Floor Plan Graphs

Department of Civil and Environmental Engineering, Seoul National University, Seoul 08826, Korea
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Academic Editors: Wolfgang Kainz and Eliseo Clementini
ISPRS Int. J. Geo-Inf. 2021, 10(2), 97; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10020097
Received: 27 January 2021 / Revised: 17 February 2021 / Accepted: 19 February 2021 / Published: 22 February 2021
This paper presents a new framework to classify floor plan elements and represent them in a vector format. Unlike existing approaches using image-based learning frameworks as the first step to segment the image pixels, we first convert the input floor plan image into vector data and utilize a graph neural network. Our framework consists of three steps. (1) image pre-processing and vectorization of the floor plan image; (2) region adjacency graph conversion; and (3) the graph neural network on converted floor plan graphs. Our approach is able to capture different types of indoor elements including basic elements, such as walls, doors, and symbols, as well as spatial elements, such as rooms and corridors. In addition, the proposed method can also detect element shapes. Experimental results show that our framework can classify indoor elements with an F1 score of 95%, with scale and rotation invariance. Furthermore, we propose a new graph neural network model that takes the distance between nodes into account, which is a valuable feature of spatial network data. View Full-Text
Keywords: floor plan analysis; vectorization; graph neural network; indoor spatial data floor plan analysis; vectorization; graph neural network; indoor spatial data
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MDPI and ACS Style

Song, J.; Yu, K. Framework for Indoor Elements Classification via Inductive Learning on Floor Plan Graphs. ISPRS Int. J. Geo-Inf. 2021, 10, 97. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10020097

AMA Style

Song J, Yu K. Framework for Indoor Elements Classification via Inductive Learning on Floor Plan Graphs. ISPRS International Journal of Geo-Information. 2021; 10(2):97. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10020097

Chicago/Turabian Style

Song, Jaeyoung, and Kiyun Yu. 2021. "Framework for Indoor Elements Classification via Inductive Learning on Floor Plan Graphs" ISPRS International Journal of Geo-Information 10, no. 2: 97. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10020097

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