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Optical Engineering

Estimation of cylinder orientation in three-dimensional point cloud using angular distance-based optimization
Author(s): Yun-Ting Su; Shuowen Hu; James S. Bethel
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Paper 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.

Paper Details

Date Published: 16 May 2017
PDF: 9 pages
Opt. Eng. 56(5) 053106 doi: 10.1117/1.OE.56.5.053106
Published in: Optical Engineering Volume 56, Issue 5
Show Author Affiliations
Yun-Ting Su, Purdue Univ. (United States)
Shuowen Hu, U.S. Army Research Lab. (United States)
James S. Bethel, Purdue Univ. (United States)

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