What is it about?
A systematic review of the computer vision-based analysis of buildings and the built environment.
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Why is it important?
This review demonstrated that studies of the built environment that adopt computer vision methods use two main approaches. The first is to automate classification tasks by mirroring established manual methods of visual analysis, such as the interpretation of architectural or urban elements. The second approach utilises machine learning as a tool for data processing and analysis to raise novel questions in architectural and urban studies, with the potential for new insights through methodological innovations.
Perspectives
Writing this article was a great effort of a transdisciplinary research team which reviewed current approaches in studies of the built environment that adopt computer vision methods from the position of both architects and computer scientists. The resulting paper combines those perspectives providing recommendations for strengthened collaboration between the disciplines.
Ms Małgorzata Barbara Starzyńska-Grześ
Royal College of Art
Read the Original
This page is a summary of: Computer Vision-based Analysis of Buildings and Built Environments: A Systematic Review of Current Approaches, ACM Computing Surveys, July 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3578552.
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