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A computer vision based approach for 3D building modelling of airborne laser scanner DSM data

机译:基于计算机视觉的机载激光扫描仪DSM数据的3D建筑物建模方法

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摘要

A computer vision based method for 3D building modelling by using stable planar regions extracted from low-spatial-resolution airborne laser scanner (ALS) data is presented. Less operator interaction (interactive processing) and an algorithm that automatically generates building parameters from digital surface models (DSM) are suggested. The stable planar region extraction approach proposed for general range data is applied to low-spatial-resolution ALS data that are resampled by a non-linear resampling method for spatial resolution enhancement. After stable planar region extraction, the roof edges formed by adjoining planes are computed by using the topologic relations and geometries of the extracted planar regions. Finally, a polyhedral description of the data is derived using the geometries of the stable planar regions, line segments of jump and/or boundary edges, and roof edges. This method is expected to be robust against noise in the DSM data. Experimental results of 3D building models show mean differences less than 1 m in the x and y dimensions and 2 m in height (z) values. The implemented techniques will present a source of valuable automatic modelling of building structures in three-dimensions and will permit modelling of conventional and non-conventional roof surfaces faithfully.
机译:提出了一种基于计算机视觉的3D建筑建模方法,该方法通过使用从低空间分辨率机载激光扫描仪(ALS)数据中提取的稳定平面区域来进行。建议较少的操作员交互(交互式处理)和一种从数字表面模型(DSM)自动生成建筑参数的算法。针对一般范围数据提出的稳定平面区域提取方法应用于低空间分辨率的ALS数据,这些数据通过非线性重采样方法进行了重采样以提高空间分辨率。在稳定的平面区域提取之后,使用提取的平面区域的拓扑关系和几何形状来计算由相邻平面形成的屋顶边缘。最后,使用稳定平面区域的几何形状,跳跃和/或边界边缘的线段以及屋顶边缘来导出数据的多面体描述。期望该方法对于DSM数据中的噪声具有鲁棒性。 3D建筑模型的实验结果表明,x和y尺寸的平均差小于1 m,高度(z)值的平均差小于2 m。所实施的技术将为三维结构的建筑物自动建模提供有价值的资源,并将忠实地对常规和非常规屋顶表面进行建模。

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