Procedural Roof Generation From a Single Satellite Image
Procedural Roof Generation From a Single Satellite Image
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DOI：
10.1111/cgf.14472
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发表时间：
2022-05
影响因子：
2.5
通讯作者：
Xiaowei Zhang;Daniel G. Aliaga
中科院分区：
文献类型：
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作者：
Xiaowei Zhang;Daniel G. Aliaga
城市程序建模受益于深度学习和计算机图形学的最新进展。然而，很少有方法(如果有的话)能从单一的头顶卫星图像自动生成程序建筑屋顶模型。大规模屋顶建模对于城市内容创建和城市规划中的各种应用(例如，太阳能电池板规划、供暖/制冷/降雨建模)非常重要。虽然仅从卫星图像建模的诱惑力是显而易见的，但不幸的是，从卫星图像获得的结构往往是低分辨率、噪声和严重遮挡的，因此很难获得清晰和完整的城市结构视图。在这篇文章中，我们提出了一个框架，它通过明确识别潜在的建筑形状和屋顶结构的紧凑空间来利用人造建筑和屋顶中存在的固有结构。然后，我们利用这个相对紧凑的空间和一个结合了过程建模和深度学习的双组件解决方案。具体地说，我们使用建筑物分解组件将建筑物分割成屋顶部分，并以程序格式预测规则化的建筑物足迹，并使用屋顶脊检测组件通过估计程序屋顶脊参数来细化单个屋顶部分。我们对多个卫星数据集的定性和定量评估表明，我们的方法优于各种最先进的方法。
Urban procedural modeling has benefited from recent advances in deep learning and computer graphics. However, few, if any, approaches have automatically produced procedural building roof models from a single overhead satellite image. Large‐scale roof modeling is important for a variety of applications in urban content creation and in urban planning (e.g., solar panel planning, heating/cooling/rainfall modeling). While the allure of modeling only from satellite images is clear, unfortunately structures obtained from the satellite images are often in low‐resolution, noisy and heavily occluded, thus getting a clean and complete view of urban structures is difficult. In this paper, we present a framework that exploits the inherent structure present in man‐made buildings and roofs by explicitly identifying the compact space of potential building shapes and roof structures. Then, we utilize this relatively compact space with a two‐component solution combining procedural modeling and deep learning. Specifically, we use a building decomposition component to separate the building into roof parts and predict regularized building footprints in a procedural format, and use a roof ridge detection component to refine the individual roof parts by estimating the procedural roof ridge parameters. Our qualitative and quantitative assessments over multiple satellite datasets show that our method outperforms various state‐of‐the‐art methods.