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- W4285408249 abstract "In the context of Smart Cities digital transformation, the field of 3D city modelling has attracted a growing interest for representing the city digital twin. This paper presents a method for producing a 3D city model with photorealistic rooftop textures extracted from aerial images, as well as the integration of the 3D city model into an open-source Smart City framework. The proposed solution provides a smart visualization of 3D city entities integrated with a large variety of Smart City data (coming, for instance, from IoT Devices which generate time-series data, heatmaps, geometries and shapes related to traffic flows, bus routes, cycling paths etc.). The proposed method for rooftop detection and alignment follows a deep learning approach based on U-Net architecture, and it has been validated against a manually created ground-truth of 50 buildings scattered uniformly on the covered area. The solution is implemented in the open-source Snap4City Smart City platform." @default.
- W4285408249 created "2022-07-14" @default.
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- W4285408249 date "2022-06-01" @default.
- W4285408249 modified "2023-10-16" @default.
- W4285408249 title "A Photorealistic 3D City Modeling Framework for Smart City Digital Twin" @default.
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- W4285408249 doi "https://doi.org/10.1109/smartcomp55677.2022.00071" @default.
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