Window to Wall Ratio Detection using SegFormer
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866914824533835776 |
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| author | De Simone, Zoe Biswas, Sayandeep Wu, Oscar |
| author_facet | De Simone, Zoe Biswas, Sayandeep Wu, Oscar |
| contents | Window to Wall Ratios (WWR) are key to assessing the energy, daylight and ventilation performance of buildings. Studies have shown that window area has a large impact on building performance and simulation. However, data to set up these environmental models and simulations is typically not available. Instead, a standard 40% WWR is typically assumed for all buildings. This paper leverages existing computer vision window detection methods to predict WWR of buildings from external street view images using semantic segmentation, demonstrating the potential for adapting established computer vision technique in architectural applications |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_02706 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Window to Wall Ratio Detection using SegFormer De Simone, Zoe Biswas, Sayandeep Wu, Oscar Computer Vision and Pattern Recognition Machine Learning Window to Wall Ratios (WWR) are key to assessing the energy, daylight and ventilation performance of buildings. Studies have shown that window area has a large impact on building performance and simulation. However, data to set up these environmental models and simulations is typically not available. Instead, a standard 40% WWR is typically assumed for all buildings. This paper leverages existing computer vision window detection methods to predict WWR of buildings from external street view images using semantic segmentation, demonstrating the potential for adapting established computer vision technique in architectural applications |
| title | Window to Wall Ratio Detection using SegFormer |
| topic | Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2406.02706 |