In industrial facilities, there are various types of equipment composed of surfaces that have a high degree of freedom. Rotational surfaces and generalized cylinders are often used for equipment handling liquids and gases. In this paper, we propose methods for reconstructing rotational surfaces and generalized cylinders from noisy and incomplete point-clouds captured by a terrestrial laser scanner. In our method, we convert point-clouds into wireframe models and calculate the intersection points with section planes. Then, we extract ellipses from the intersection points on each section plane and reconstruct the rotational surfaces and generalized cylinders using the extracted ellipses. We also propose a method for subdividing a rotational surface into primitive surfaces. We evaluated our method using actual point-clouds of engineering facilities and confirmed that our method could successfully reconstruct rotational surfaces and generalized cylinders.

1. [1] F. Bosché, “Automated recognition of 3D CAD model objects in laser scans and calculation of as-built dimensions for dimensional compliance control in construction,” Advanced Engineering Informatics, Vol.24, No.1, pp. 107-118, 2010.
2. [2] A. Bey, R. Chaine, R. Marc, G. Thibault, and S. Akkouche, “Reconstruction of consistent 3D CAD models from point cloud data using a priori CAD models,” ISPRS Workshop on Laser Scanning, Vol.1, 2011.
3. [3] D. Huber, B. Akinci, A. A. Oliver, E. Anil, B. E. Okorn, and X. Xiong, “Methods for automatically modeling and representing as-built building information models,” Proc. of the NSF CMMI Research Innovation Conf., 2011.
4. [4] E. B. Anil, P. Tang, B. Akinci, and D. Huber, “Deviation analysis method for the assessment of the quality of the as-is Building Information Models generated from point cloud data,” Automation in Construction, Vol.35, pp. 507-516, 2013.
5. [5] H. C. Nguyen and B. R. Lee, “3D model reconstruction system development based on laser-vision technology,” Int. J. Automation Technol., Vol.10, No.5, pp. 813-820, 2016.
6. [6] G. Lukács, R. Martin, and D. Marshall, “Faithful least-squares fitting of spheres, cylinders, cones and tori for reliable segmentation,” European Conf. on Computer Vision, pp. 671-686, 1998.
7. [7] R. Schnabel, R. Wahl, and R. Klein, “Efficient RANSAC for point-cloud shape detection,” Computer Graphics Forum, Vol.26. No.2, pp. 214-226, 2007.
8. [8] Y. Li, W. Xiaokun, Y. Chrysathou, A. Sharf, D. Cohen-Or, and N. Mitra, “Globfit: Consistently fitting primitives by discovering global relations,” ACM Trans. on Graphics (TOG), Vol.30, No.4, 2011.
9. [9] G. Vosselman, B. G. Gorte, G. Sithole, and T. Rabbani, “Recognising structure in laser scanner point clouds,” Int. Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol.46, No.8, pp. 33-38, 2004.
10. [10] C. A. Vanegas, D. G. Aliaga, and B. Beneš, “Building reconstruction using manhattan-world grammars,” IEEE Conf. on Computer Vision and Pattern Recognition, pp. 358-365, 2010.
11. [11] P. Tang, D. Huber, B. Akinci, R. Lipman, and A. Lytle, “Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniques,” Automation in Construction, Vol.19, No.7, pp. 829-843, 2010.
12. [12] P. Musialski, P. Wonka, D. G. Aliaga, M. Wimmer, L. V. Gool, and W. Purgathofer, “A survey of urban reconstruction,” Computer Graphics Forum, Vol.32, No.6, pp. 146-177, 2013.
13. [13] A. Monszpart, N. Mellado, G. J. Brostow, and N. J. Mitra, “RAPter: rebuilding man-made scenes with regular arrangements of planes,” ACM Trans. of Graphics, Vol.34, No.4, Article No.103, 2015.
14. [14] X. Qian and X. Huang, “Reconstruction of surfaces of revolution with partial sampling,” J. of Computational and Applied Mathematics, Vol.163, No.1, pp. 211-217, 2004.
15. [15] Y. Li, H. Uchiyama, J. M. Normand, G. Moreau, H. Nagahara, and R. Taniguchi, “Real-time surface of revolution reconstruction on dense SLAM,” IEEE 2016 4th Int. Conf. on 3D Vision (3DV), pp. 28-36, 2016.
16. [16] N. D. Cornea, D. Silver, and P. Min, “Curve-skeleton properties, applications, and algorithms,” IEEE Trans. on Visualization and Computer Graphics, Vol.13, No.3, pp. 530-548, 2007.
17. [17] V. Sam, H. Kawata, and T. Kanai, “A robust and centered curve skeleton extraction from 3D point cloud,” Computer-Aided Design and Applications, Vol.9, No.6, pp. 869-879, 2012.
18. [18] J. Lee, H. Son, C. Kim, and C. Kim, “Skeleton-based 3D reconstruction of as-built pipelines from laser-scan data,” Automation in Construction, Vol.35, pp. 199-207, 2013.
19. [19] A. Tagliasacchi, H. Zhang, and D. Cohen-Or, “Curve skeleton extraction from incomplete point cloud,” ACM Trans. on Graphics (TOG), Vol.28, No.3, pp. 71:1-71:9, 2009.
20. [20] A. Chida and H. Masuda, “Reconstruction of Polygonal Prisms,” J. of Computational Design and Engineering, Vol.3, No.4, pp. 322-329, 2015.
21. [21] T. Mizoguchi, T. Kuma, Y. Kobayashi, and K. Shirai, “Manhattan-world assumption for as-built modeling industrial plant,” Key Engineering Materials, Vol.523, pp. 350-355, 2012.
22. [22] H. Masuda, T. Niwa, I. Tanaka, and R. Matsuoka, “Reconstruction of polygonal faces from large-scale point-clouds of engineering plants,” Computer-Aided Design and Applications, Vol.12, No.5, pp. 555-563, 2015.
23. [23] H. Masuda and I. Tanaka, “Extraction of surface primitives from noisy large-scale point-clouds,” Computer-Aided Design and Applications, Vol.6, No.3, pp. 387-398, 2009.
24. [24] K. Kawashima, S. Kanai, and H. Date, “As-built modeling of piping system from terrestrial laser-scanned point clouds using normal-based region growing,” J. of Computational Design and Engineering, Vol.1, No.1, pp. 13-26, 2014.