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Estimation of cylinder orientation in three-dimensional point cloud using angular distance-based optimization

机译：基于角距优化的三维点云圆柱取向估计

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摘要

Light detection and ranging (LIDAR) has become a widely used tool in remote sensing for mapping, surveying, modeling, and a host of other applications. The motivation behind this work is the modeling of piping systems in industrial sites, where cylinders are the most common primitive or shape. We focus on cylinder parameter estimation in three-dimensional point clouds, proposing a mathematical formulation based on angular distance to determine the cylinder orientation. We demonstrate the accuracy and robustness of the technique on synthetically generated cylinder point clouds (where the true axis orientation is known) as well as on real LIDAR data of piping systems. The proposed algorithm is compared with a discrete space Hough transform-based approach as well as a continuous space inlier approach, which iteratively discards outlier points to refine the cylinder parameter estimates. Results show that the proposed method is more computationally efficient than the Hough transform approach and is more accurate than both the Hough transform approach and the inlier method.
机译：光检测和测距（LIDAR）已成为遥感中用于制图，测量，建模和许多其他应用的一种广泛使用的工具。这项工作的动机是在工业现场对管道系统进行建模，在工业现场中，气瓶是最常见的图元或形状。我们专注于三维点云中的圆柱体参数估计，提出了一种基于角距离的数学公式来确定圆柱体的方向。我们在合成生成的圆柱点云（已知真实轴方向）以及管道系统的真实LIDAR数据上证明了该技术的准确性和鲁棒性。将该算法与基于离散空间Hough变换的方法以及连续空间惯性法进行了比较，该方法迭代地丢弃异常点以精炼圆柱参数估计。结果表明，该方法比Hough变换方法具有更高的计算效率，并且比Hough变换方法和Inlier方法都更加准确。

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