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TopoLAP: Topology Recovery for Building Reconstruction by Deducing the Relationships between Linear and Planar Primitives

机译:TopoLAP:通过推导线性和平面基元之间的关系进行建筑物重建的拓扑恢复

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Limited by the noise, missing data and varying sampling density of the point clouds, planar primitives are prone to be lost during plane segmentation, leading to topology errors when reconstructing complex building models. In this paper, a pipeline to recover the broken topology of planar primitives (TopoLAP) is proposed to reconstruct level of details 3 (LoD3) models. Firstly, planar primitives are segmented from the incomplete point clouds and feature lines are detected both from point clouds and images. Secondly, the structural contours of each plane segment are reconstructed by subset selection from intersections of these feature lines. Subsequently, missing planes are recovered by plane deduction according to the relationships between linear and planar primitives. Finally, the manifold and watertight polyhedral building models are reconstructed based on the optimized PolyFit framework. Experimental results demonstrate that the proposed pipeline can handle partial incomplete point clouds and reconstruct the LoD3 models of complex buildings automatically. A comparative analysis indicates that the proposed method performs better to preserve sharp edges and achieves a higher fitness and correction rate than rooftop-based modeling and the original PolyFit algorithm.
机译:受噪声,数据丢失和点云采样密度变化的限制,平面图元在平面分割期间容易丢失,从而在重建复杂的建筑模型时导致拓扑错误。在本文中,提出了恢复平面图元的破碎拓扑的管道(TopoLAP),以重建细节级别3(LoD3)模型。首先,从不完整的点云中分割出平面图元,并从点云和图像中检测特征线。其次,通过从这些特征线的交点进行子集选择来重建每个平面段的结构轮廓。随后,根据线性图元和平面图元之间的关系,通过平面推导来恢复缺失的平面。最后,在优化的PolyFit框架的基础上重建了流形和水密多面体建筑模型。实验结果表明,提出的管道可以处理部分不完整的点云,并可以自动重建复杂建筑物的LoD3模型。对比分析表明,与基于屋顶的建模和原始的PolyFit算法相比,所提出的方法在保留锐利边缘方面性能更好,并且具有更高的适应度和校正率。

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