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Structure-aware Building Mesh Polygonization
ISPRS Journal of Photogrammetry and Remote Sensing ( IF 10.6 ) Pub Date : 2020-08-05 , DOI: 10.1016/j.isprsjprs.2020.07.010
Vasileios Bouzas , Hugo Ledoux , Liangliang Nan

We introduce a novel approach for the polygonization of Multi-view Stereo (MVS) meshes of buildings, which results in compact and topologically valid models. The main characteristic of our method is structure awareness, i.e., the recovery and preservation of the initial mesh primitives and their adjacencies. Our proposed methodology consists of three main stages: (a) primitive detection via mesh segmentation, (b) encoding of primitive adjacencies into a graph, and (c) polygonization. Polygonization is based on the approximation of the original mesh with a candidate set of planar polygonal faces. On this candidate set, we apply a binary labelling formulation to select and assemble an optimal set of faces under hard constraints that ensure that the final model is both manifold and watertight. Experiments on various building models demonstrate that our simplification method can produce simpler representations for both closed and open building meshes. Furthermore, these representations highly conform to the initial structure and are ready to be used for spatial analysis. The source code of this work is freely available at .



中文翻译:

结构感知的建筑网格多边形

我们介绍了一种用于建筑物的多视图立体(MVS)网格的多边形化的新颖方法,该方法可生成紧凑且在拓扑上有效的模型。我们方法的主要特征是结构意识,即恢复和保存初始网格图元及其邻接关系。我们提出的方法包括三个主要阶段:(a)通过网格分割进行原始检测,(b)将原始邻接编码到图中,以及(c)多边形化。多边形化基于原始网格与一组候选平面多边形的近似值。在此候选集上,我们应用二进制标注公式来选择和组合在严格约束下的最佳面孔集,以确保最终模型既具有流形又具有水密性。在各种建筑模型上进行的实验表明,我们的简化方法可以为封闭和开放的建筑网格生成更简单的表示。此外,这些表示非常符合初始结构,可以用于空间分析。这项工作的源代码可在上免费获得。

更新日期:2020-08-05
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