| id |
caadria2021_155 |
| authors |
Maeng, Hoyoung and Hyun, Kyung Hoon |
| year |
2021 |
| title |
Data-Driven Analysis of Spatial Patterns through Large-Scale Datasets of Building Floor Plan |
| source |
A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 301-310 |
| doi |
https://doi.org/10.52842/conf.caadria.2021.1.301
|
| summary |
This paper introduces a unique quantitative analysis method and results that are differentiated from those in existing studies. We analyzed five types of information in floor plan images: the silhouette, number of rooms, room area, and direct and indirect room connectivity. Furthermore, the analysis used a large-scale apartment unit dataset consisting of 33,892 units. We present convincing and objective spatial pattern analysis results of Korean apartments by quantitatively analyzing a large-scale dataset. It is expected that the analysis results will clarify the characteristics of the residential environment of Korean apartments. The results suggest that changes in lifestyles lead to the modularization of bedrooms, increased numbers of private bathrooms and balconies with corridors as junctions, and the diversification of room layouts. |
| keywords |
Floor Plan Analysis; Design Quantification; Residential Layout; Spatial Pattern Analysis; Semantic Fingerprint |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (2,243,535 bytes) |
| references |
Content-type: text/plain
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, Proceedings of the IEEE International Conference on Computer Vision (ICCV) 2017
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, Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) 2019
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| last changed |
2022/06/07 07:59 |
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