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3D Building Roof Modeling by Optimizing Primitive’s Parameters Using Constraints from LiDAR Data and Aerial Imagery

机译:通过使用来自LiDAR数据和航空影像的约束来优化基元的参数来进行3D建筑屋顶建模

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In this paper, a primitive-based 3D building roof modeling method, by integrating LiDAR data and aerial imagery, is proposed. The novelty of the proposed modeling method is to represent building roofs by geometric primitives and to construct a cost function by using constraints from both LiDAR data and aerial imagery simultaneously, so that the accuracy potential of the different sensors can be tightly integrated for the building model generation by an integrated primitive’s parameter optimization procedure. To verify the proposed modeling method, both simulated data and real data with simple buildings provided by ISPRS (International Society for Photogrammetry and Remote Sensing), were used in this study. The experimental results were evaluated by the ISPRS, which demonstrate the proposed modeling method can integrate LiDAR data and aerial imagery to generate 3D building models with high accuracy in both the horizontal and vertical directions. The experimental results also show that by adding a component, such as a dormer, to the primitive, a variant of the simple primitive is constructed, and the proposed method can generate a building model with some details.
机译:本文提出了一种结合LiDAR数据和航空影像的基于原始的3D建筑屋顶建模方法。所提出的建模方法的新颖性在于用几何图元表示建筑物屋顶,并同时利用来自LiDAR数据和航拍图像的约束条件来构建成本函数,从而可以将不同传感器的精度潜力紧密地集成到建筑模型中通过集成原语的参数优化过程生成。为了验证所提出的建模方法,本研究使用了模拟数据和由ISPRS(国际摄影测量与遥感学会)提供的具有简单建筑物的真实数据。 ISPRS对实验结果进行了评估,结果表明所提出的建模方法可以将LiDAR数据与航拍图像集成,以在水平和垂直方向上生成高精度的3D建筑模型。实验结果还表明,通过向原语中添加诸如dormer之类的组件,可以构造简单原语的变体,并且所提出的方法可以生成具有一些细节的构建模型。

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