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Automated recognition of 3D pipelines from point clouds

机译:从点云的3D管道自动识别

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摘要

This study proposes a method for detecting and reconstructing pipelines from a 3D point cloud. First, the method extracts points on cylindrical objects using various properties computed with the principal curvatures. Next, the possible radii of the cylinders in the point cloud are estimated using a histogram constructed with the radii of the curvature at each point. Once the candidate radii are obtained, spheres are estimated using a RANdom SAmple Consensus-based algorithm, whose centroids are processed to find the orientation and centerline of each cylinder. The nearest cylindrical components which are detected are then analyzed to establish connectivity to determine how they are arranged in space. Depending on the type of connectivity, elbows and/or T-junctions are used to connect the cylindrical elements to form pipelines. The proposed method was tested with synthetic and scanned point clouds and demonstrated better performance than that of the existing methods.
机译:该研究提出了一种从3D点云检测和重建管道的方法。 首先,该方法利用具有主曲率计算的各种特性提取圆柱形物体的点。 接下来,使用在每个点处的曲率的半径构造的直方图估计点云中的汽缸的可能半径。 一旦获得候选半径,使用基于随机的样本共有的算法估计球体,其被处理质心来找到每个气缸的方向和中心线。 然后分析检测到的最接近的圆柱形部件以建立连接,以确定它们在空间中的排列方式。 取决于连接的类型,肘部和/或T型连接用于连接圆柱形元件以形成管道。 用合成和扫描点云测试所提出的方法,并表现出比现有方法的性能更好。

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