Non-Uniform B-Spline Surface Fitting from Unordered 3D Point Clouds for As-Built Modeling

Computer-Aided Civil and Infrastructure Engineering

Volumn 31, Issue 7, 2016, Pages 483-498

  Dimitrov, Andrey ^a   Gu, Rongqi ^b   Golparvar Fard, Mani ^b  

^a Fu Foundation School of Engineering and Applied Science   (United States)

^b University of Illinois at Urbana Champaign   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CURVE FITTING; MAPPING; SPLINES; THREE DIMENSIONAL COMPUTER GRAPHICS;

ENERGY PERFORMANCE; ENGINEERING APPLICATIONS; NONUNIFORM B SPLINE; STATE-OF-THE-ART METHODS; SUPERVISED METHODS; THREE DIMENSIONAL MAPPING; TOPOLOGICAL VARIATIONS; UNIFORM B-SPLINES;

INTERPOLATION;

ENGINEERING; MAPPING; OPTIMIZATION; PARAMETERIZATION; THREE-DIMENSIONAL MODELING;

EID: 84955142057     PISSN: 10939687     EISSN: 14678667     Source Type: Journal    
DOI: 10.1111/mice.12192     Document Type: Article

References (40)

1. Ahmed, M., Haas, C. & Haas, R. (2014), Automatic detection of cylindrical objects in built facilities, Computing Civil Engineering, 28(3), 04014009.
2. Autodesk. (2014), Autodesk Recap Pro. Available at: http://www.autodesk.com/products/recap.
3. Azariadis, P. N. (2004), Parameterization of clouds of unorganized points using dynamic base surfaces, Computer-Aided Design, 36(7), 607-23.
4. Barhak, J. & Fischer, A. (2001), Parameterization and reconstruction from 3D scattered points based on neural network and PDE techniques, IEEE Transactions on Visualization and Computer Graphics, 7(1), 1-16.
5. Bo, P., Ling, R. & Wang, W. (2012), A revisit to fitting parametric surfaces to point clouds, Computers & Graphics, 36(5), 534-40.
6. Bosché, F., Ahmed, M., Turkan, Y., Haas, C. T. & Haas, R. (2015), The value of integrating Scan-to-BIM and Scan-vs-BIM techniques for construction monitoring using laser scanning and BIM: the case of cylindrical MEP components, Automation in Construction, 49, 201-13.
7. Budroni, A. & Boehm, J. (2010), Automated 3D reconstruction of interiors from point clouds, International Journal of Architectural Computing, Multi-Science, 8(1), 55-73.
8. buildingSMART. (2009), IFC2x4. Available at: http://www. buildingsmart-tech.org/specifications/ifc-releases/ifc2x4.
9. Chen, X., Golovinskiy, A. & Funkhouser, T. (2009), A benchmark for (3D) mesh segmentation, ACM Transactions on Graphics, 28(3).
10. Chiozzi, A., Malagù, M., Tralli, A. & Cazzani, A. (2015), ArchNURBS: NURBS-based tool for the structural safety assessment of masonry arches in MATLAB, Journal of Computing in Civil Engineering, 10.1061/(ASCE)CP.1943-5487.0000481, 04015010.
11. Dan, J. & Lancheng, W. (2006), An algorithm of NURBS surface fitting for reverse engineering. International Journal of Advanced Manufacturing Technology, 31(1-2), 92-7.
12. Dierckx, P. (1993), Curve and Surface Fitting with Splines, Oxford University Press, Inc.
13. Dimitrov, A. & Golparvar-Fard, M. (2015), Segmentation of building point cloud models including detailed architectural/structural features and mep systems, Automation in Construction, 51, 32-45.
14. Douillard, B., Underwood, J., Kuntz, N., Vlaskine, V., Quadros, A., Morton, P. & Frenkel, A. (2011), On the segmentation of 3D LIDAR point clouds, 2011 IEEE Robotics and Automation, 2798-805.
15. Huang, Q. & Dom, B. (1995), Quantitative methods of evaluating image segmentation, Proceedings of the International Conference on Image Processing, 53-6.
16. Jian, S. Y. W. H. L. (2004), Research on the method of accurate NURBS surface fitting to scattered points, Chinese Journal of Mechanical Engineering, 3, 002.
17. Koch, K. R. (2009), Identity of simultaneous estimates of control points and of their estimates by the lofting method for NURBS surface fitting, Proceedings of the International Journal of Advanced Manufacturing Technology, 44(11-12), 1175-80.
18. Kubit. (2014), PointSense buildings. Available at: http://us.kubit-software.com/CAD/Products/PointSense.
19. Lai, Y.-K., Hu, S.-M. & Pottmann, H. (2006), Surface fitting based on a feature sensitive parametrization, Computer-Aided Design, 38(7), 800-07.
20. Liebich. (2010), Unveiling IFC2x4-The next generation of OPENBIM, " in Proceedings of the 2010 CIB W78 Conference.
21. Liu, Y., Pottmann, H. & Wang, W. (2006), Constrained 3D shape reconstruction using a combination of surface fitting and registration, Computer-Aided Design, 38(6), 572-83.
22. Morwald, T., Richtsfeld, A., Prankl, J., Zillich, M. & Vincze, M. (2013), Geometric data abstraction using B-splines for range image segmentation, in Proceedings of the 2013 IEEE International Conference on Robotics and Automation (ICRA), 148-153.
23. Moret, B. M. E. & Shapiro, H. D. (1994), An empirical assessment of algorithms for constructing a minimum spanning tree, Monographs in Discrete Mathematics and Theoretical Computer Science, 15, 99-117.
24. Pătrăucean, V., Armeni, I., Nahangi, M., Yeung, J., Brilakis, I. & Haas, C. (2015), State of research in automatic as-built modelling. Advanced Engineering Informatics, doi:10.1016/j.aei.2015.01.001.
25. Peternell, M. (2004), Developable surface fitting to point clouds, Computer-Aided Geo Design, 21(8), 785-803.
26. Piegl, L. A. & Tiller, W. (1997), The NURBS Book. Springer.
27. Rabbani, T., van Den Heuvel, F. & Vosselmann, G. (2006), Segmentation of point clouds using smoothness constraint, International Archives of Photogrammetry, Remote Sensing & Spatial Info Science, 36(5), 248-53.
28. Radopoulou, S., Sun, M., Dai, F., Brilakis, I. & Savarese, S. (2012), Testing of depth-encoded though voting for infrastructure object detection, Computing in Civil Engineering, 309-16.
29. Richtsfeld, A., Mörwald, T., Prankl, J., Balzer, J., Zillich, M. & Vincze, M. (2012), Towards scene understanding-object segmentation using RGBD-images, Computer Vision Winter Workshop.
30. Richtsfeld, A., Mörwald, T., Prankl, J., Zillich, M., & Vincze, M. (2014). Learning of perceptual grouping for object segmentation on RGB-D data. Journal of Visual Communication and Image Representation, 25(1), 64-73.
31. Son, H., Kim, C. & Kim, C. (2013). Fully automated as-built 3D pipeline segmentation based on curvature computation from laser-scanned data, Computing in Civil Engineering, 765-72.
32. Tang, P., Huber, D., Akinci, B., Lipman, R. & Lytle, A. (2010). Automatic reconstruction of as-built building information models from laser-scanned point clouds: A review of related techniques, Journal of Automation in Construction, 19(7), 829-43.
33. Trimble. (2014), RealWorks. Available at: http://www.trimble.com/3d-laser-scanning/realworks.aspx?dtID = overview&.
34. Valero, E., Adan, A., Huber, D. & Cerrada, C. (2011), Detection, modeling, and classification of moldings for automated reverse engineering of buildings from 3D data, in Proceedings of the 28th International Symposium on Automation and Robotics in Construction, 546-51.
35. Weiss, V., Andor, L., Renner, G. & Várady, T. (2002), Advanced surface fitting techniques, Computer Aided Geometric Design, 19(1), 19-42.
36. Wu, C., Agarwal, S., Curless, B. & Seitz, S. M. (2012), Schematic surface reconstruction, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1498-505.
37. Xie, W.-C., Zou, X.-F., Yang, J.-D. & Yang, J.-B. (2012), Iteration and optimization scheme for the reconstruction of 3D surfaces based on non-uniform rational B-splines, Computer-Aided Design, 44(11), 1127-40.
38. Xiong, X., Adan, A., Akinci, B. & Huber, D. (2013). Automatic creation of semantically rich 3D building models from laser scanner data, Automation in Construction, 31, 325-37.
39. Yang, J., and Shi, Z. (2014), Image-based 3D semantic modeling of building facade, Computer Vision and Graphics, Springer, 661-71.
40. Zhang, G., Vela, P. A., Karasev, P. & Brilakis, I. (2015), A sparsity-inducing optimization-based algorithm for planar patches extraction from noisy point-cloud data, Computer-Aided Civil and Infrastructure Engineering, 30(2), 85-102.