Browse > Article
http://dx.doi.org/10.15701/kcgs.2018.24.5.11

A Modified Method for Registration of 3D Point Clouds with a Low Overlap Ratio  

Kim, Jigun (Hyundai Steel)
Lee, Junhee (The School of Mechanical Engineering, Gwangju Institute of Science and Technology)
Park, Sangmin (The School of Mechanical Engineering, Gwangju Institute of Science and Technology)
Ko, Kwanghee (The School of Mechanical Engineering, Gwangju Institute of Science and Technology)
Publication Information
Journal of the Korea Computer Graphics Society / v.24, no.5, 2018 , pp. 11-19 More about this Journal
Abstract
In this paper, we propose an algorithm for improving the accuracy and rate of convergence when two point clouds with noise and a low overlapping area are registered to each other. We make the most use of the geometric information of the underlying geometry of the point clouds with noise for better accuracy. We select a reasonable region from the noisy point cloud for registration and combine a modified acceleration algorithm to improve its speed. The conventional accuracy improvement method was not possible in a lot of noise, this paper resolves the problem by selecting the reasonable region for the registration. And this paper applies acceleration algorithm for a clone to low overlap point cloud pair. A simple algorithm is added to the conventional method, which leads to 3 or 4 times faster speed. In conclusion, this algorithm was developed to improve both the speed and accuracy of point cloud registration in noisy and low overlap case.
Keywords
Iterative closest point (ICP); Point cloud registration; Low overlap point cloud;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 F. Deng, "Registration between Multiple Laser Scanner Data Sets," Laser Scanning, Theory and Applications, pp.449-472, 2011.
2 J. Kim, "A modified Method to Accelerate for Registration of 3D Point Cloud with low Overlapping Ratios for Rigid Body," M.Sc. Thesis, School of Mechanical Engineering, Gwangju Institute of Science and Technology, 2018.
3 P. Besl and N. McKay, "A method for registration of 3-d shapes," Pattern Analysis and Machine Intelligence, 14 (2) pp.239-256, 1992.   DOI
4 J. Lee and K. Ko, "Utilization of GPS and IMU Sensors in the Initial Registration of Two Point Clouds," Korean Journal of Computational Design and Engineering, 23(2), pp. 173-183, 2018.   DOI
5 K. Pulli, "Multiview registration for large data sets," 3-D Digital Imaging and Modeling, pp. 160-168, 1999.
6 D. Yun, S. Choi, S. Kim and K. Ko, "Registration of multiview point clouds for application to ship fabrication," Graphical Models, 90, pp.1-12, 2017.   DOI
7 Y. Chen and G. Medioni, "Object modeling by registration of multiple range images," Image and Vision Computing , 10 (3) pp.145-155, 1992.   DOI
8 B. Horn, "Closed-form solution of absolute orientation using unit quaternions," Journal of the Optical Society of America A, 4 (4) pp.629-642, 1987.   DOI
9 T. Masuda, K. Sakaue and N. Yokoya, "Registration and integration of multiple range images for 3-d model construction," Pattern Recognition , pp.879-883, 1996.
10 Y.Wu,W.Wang, K. Lu, Y.Wei and Z. Chen, "A new method for registration of 3d point sets with low overlapping ratios," Procedia CIRP conference on Computer Aided Tolerancing, 27, pp.202-206, 2015.
11 W. Li and P. Song, "A modified icp algorithm based on dynamic adjustment factor for registration of point cloud and cad model," Pattern Recognition Letters, 65, pp.88-94, 2015.   DOI
12 L. Stefano, S. Mattoccia and F. Tombari, "ZNCC-based template matching using bounded partial correlation," Pattern Recognition Letters, 26, pp.2129-2134, 2005.   DOI
13 R. Fisher, "From Surface to Objects: Computer Vision and Three Dimensional Scene Analysis," John Wiley and Sons, 1989.