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NTIS 바로가기한국정보통신학회논문지 = Journal of the Korea Institute of Information and Communication Engineering, v.25 no.6, 2021년, pp.799 - 806
임석현 (Innovation Center, 3D Systems Korea)
The transforming process of point clouds with its local coordinates into a global coordinate is called registration. In contrast to the local registration which takes a long time to calculate and performs precision registration after initial rough positioning, the global registration calculates the ...
S. Lim, "Effective criterion for evaluating registration accuracy," Journal of the Korea Institute of Information and Communication Engineering, vol. 25, no. 5, pp. 652-658, 2021.
K. Kwon, "A weighted points registration method to analyze dimensional errors occurring during shipbuilding process," Transactions of the Society of CAD/CAM Engineers, vol. 21, no. 2, pp. 151-158, 2016.
Z. H. Nejad and M. Nasri, "An adaptive image registration method based on SIFT features and RANSAC transform," Computers & Electrical Engineering, vol. 62, pp. 524-537, 2017.
M. He, L. Huang, B. Zhao, B. Chen, and B. Hu, "Advanced functional materials in solid phase extraction for ICP-MS determination of trace elements and their species - A review," Analytica Chimica Acta, vol. 973, no. 22 pp. 1-24, 2017.
Z. Wu, H. Chen, S. Du, M. Fu, N. Zhou, and N. Zheng, "Correntropy based scale ICP algorithm for robust point set registration," Pattern Recognition, vol. 93, pp. 14-24, 2019.
J. Yang, H. Li, D. Campbell, and Y. Jia, "Go-ICP: A globally optimal solution to 3D ICP pointset registration," in Proceedings IEEE/CVF International Conference on Computer Vision, 2016.
Q. Y. Zhou, P. Jaesik, and K. Vladlen, "Fast global registration," in Proceedings European Conference on Computer Vision, Netherlands, 2016.
Open3D project [Internet]. Available: http://www.open3d.org/.
R. B. Rusu, N. Blodow, and M. Beetz, "Fast point feature histograms (FPFH) for 3D registration," in Proceedings IEEE International Conference on Robotics and Automation, 2009.
J. T. Barron, "A general and adaptive robust loss function," in Proceeding of Computer Vision and Pattern Recognition, USA, pp. 4331-4339, 2019.
Stanford University 3D Scan Repository [Internet]. Available: http://graphics.stanford.edu/data/.
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