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Reconstructing building genealogy with visual intelligence
Xuan Xue1,2, Yaotian Yang3, Zihui Tian2
1School of Architecture and Urban Planning, Suzhou University of Science and Technology, Suzhou, China.
Nature Communications
|June 16, 2026
Summary
This study introduces a computational framework using visual intelligence to classify historic Singapore shophouses, revealing new insights into their multi-ethnic origins beyond traditional chronological orders.
Area of Science:
- Computational architecture
- Digital humanities
- Architectural history
Background:
- Vernacular building studies traditionally rely on manual methods, risking selective interpretation.
- Existing classifications of Singapore shophouses may not fully capture their complex history.
Purpose of the Study:
- To develop and apply a computational framework integrating visual intelligence for reconstructing building genealogy.
- To perform stylistic classification of Singapore shophouses using image analysis.
- To offer a critical perspective on the multi-ethnic character of these historic buildings.
Main Methods:
- A computational framework was developed, leveraging visual intelligence for data interpretation.
- The framework was applied to 1,276 frontage images of historic shophouses in Singapore's Chinatown.
- Image analysis techniques were used for stylistic classification.
Main Results:
- The framework enabled a classification of Singapore shophouses that moves beyond established chronological orders.
- New perspectives on the multi-ethnic influences on shophouse architecture were identified.
- The study demonstrated the effectiveness of computational methods in architectural analysis.
Conclusions:
- Computational frameworks with visual intelligence can enhance the study of vernacular architecture.
- This approach provides a more nuanced understanding of Singapore's built heritage.
- Interdisciplinary collaboration between computer science and human settlement studies yields significant insights.
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