Advanced SearchSearch Tips
Matching for Cylinder Shape in Point Cloud Using Random Sample Consensus
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
  • Journal title : Journal of KIISE
  • Volume 43, Issue 5,  2016, pp.562-568
  • Publisher : Korean Institute of Information Scientists and Engineers
  • DOI : 10.5626/JOK.2016.43.5.562
 Title & Authors
Matching for Cylinder Shape in Point Cloud Using Random Sample Consensus
Jin, YoungHoon;
Point cloud data can be expressed in a specific coordinate system of a data set with a large number of points, to represent any form that generally has different characteristics in the three-dimensional coordinate space. This paper is aimed at finding a cylindrical pipe in the point cloud of the three-dimensional coordinate system using RANSAC, which is faster than the conventional Hough Transform method. In this study, the proposed cylindrical pipe is estimated by combining the results of parameters based on two mathematical models. The two kinds of mathematical models include a sphere and line, searching the sphere center point and radius in the cylinder, and detecting the cylinder with straightening of center. This method can match cylindrical pipe with relative accuracy; furthermore, the process is rapid except for normal estimation and segmentation. Quick cylinders matching could benefit from laser scanning and reverse engineering construction sectors that require pipe real-time estimates.
point cloud;RANSAC;iterative method;matching;3D scanner;building;
 Cited by
Rabbani. Tahir, Frank van den Heuvel, and G. Vosselmann, "Segmentation of point clouds using smoothness constraint," International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 36.5 pp. 248-253, 2006.

Abuzaina. Anas, Mark S. Nixon, and John N. Carter, "Sphere detection in kinect point clouds via the 3d hough transform," In Computer Analysis of Images and Patterns, Springer Berlin Heidelberg, pp. 290-297, 2013.

Zhang. Ning, "Plane Fitting on Airborne Laser Scanning Data Using RANSAC," Lunds Tekniska Hogskola, 2011.

Garcia. Sergio, "Fitting primitive shapes to point clouds for robotic grasping," Master of Science Thesis. School of Computer Science and Communication, Royal Institute of Technology, Stockholm, Sweden, 2009.

Su. Yun-Ting, and James Bethel, "Detection and robust estimation of cylinder features in point clouds," Proc. of ASPRS Annual Conference on Opportunities for Emerging Geospatial Technologies, 2010.

JONES. Brian, and Michel AOUN, "Learning 3D Point Cloud Histograms," 2009.

Fischler. Martin A, and Robert C. Bolles, "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography," Communications of the ACM 24, No. 6, pp. 381-395, 1981. crossref(new window)

Raguram. Rahul, Jan-Michael Frahm, and Marc Pollefeys, "A comparative analysis of RANSAC techniques leading to adaptive real-time random sample consensus," Computer Vision-ECCV 2008, Springer Berlin Heidelberg, pp. 500-513. 2008.

Smith. Lindsay I, "A tutorial on principal components analysis," Cornell University, USA 51, 2002.

Person. K, "On Lines and Planes of Closest Fit to System of Points in Space," Philosophical Magazine, Vol. 2, pp. 559-572, 1901. crossref(new window)