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首页> 外文期刊>Visualization and Computer Graphics, IEEE Transactions on >Automatic Extraction of Manhattan-World Building Masses from 3D Laser Range Scans
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Automatic Extraction of Manhattan-World Building Masses from 3D Laser Range Scans

机译：从3D激光测距扫描自动提取曼哈顿世界建筑质量

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摘要

We propose a novel approach for the reconstruction of urban structures from 3D point clouds with an assumption of Manhattan World (MW) building geometry; i.e., the predominance of three mutually orthogonal directions in the scene. Our approach works in two steps. First, the input points are classified according to the MW assumption into four local shape types: walls, edges, corners, and edge corners. The classified points are organized into a connected set of clusters from which a volume description is extracted. The MW assumption allows us to robustly identify the fundamental shape types, describe the volumes within the bounding box, and reconstruct visible and occluded parts of the sampled structure. We show results of our reconstruction that has been applied to several synthetic and real-world 3D point data sets of various densities and from multiple viewpoints. Our method automatically reconstructs 3D building models from up to 10 million points in 10 to 60 seconds.
机译：在提出曼哈顿世界（MW）建筑几何形状的假设下，我们提出了一种从3D点云重建城市结构的新颖方法。即场景中三个相互正交方向的优势。我们的方法分两个步骤进行。首先，根据MW假设将输入点分类为四种局部形状类型：墙，边，角和边角。分类点被组织成一组相连的群集，从中提取体积描述。 MW假设使我们能够可靠地识别基本形状类型，描述边界框内的体积，并重建采样结构的可见部分和封闭部分。我们展示了我们的重构结果，该结果已应用于多种密度且从多个角度出发的多个合成和真实世界3D点数据集。我们的方法可在10到60秒内自动从多达1千万个点重建3D建筑模型。

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