16 May 2017 Estimation of cylinder orientation in three-dimensional point cloud using angular distance-based optimization
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Abstract
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.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Yun-Ting Su, Yun-Ting Su, Shuowen Hu, Shuowen Hu, James S. Bethel, James S. Bethel, } "Estimation of cylinder orientation in three-dimensional point cloud using angular distance-based optimization," Optical Engineering 56(5), 053106 (16 May 2017). https://doi.org/10.1117/1.OE.56.5.053106 . Submission: Received: 10 January 2017; Accepted: 26 April 2017
Received: 10 January 2017; Accepted: 26 April 2017; Published: 16 May 2017
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