Abstract
Reconstruction of hand-held laser scanner data is used in industry primarily for reverse engineering. Traditionally, scanning and reconstruction are separate steps. The operator of the laser scanner has no feedback from the reconstruction results. On-line reconstruction of the CAD geometry allows for such an immediate feedback.
We propose a method for on-line segmentation and reconstruction of CAD geometry from a stream of point data based on means that are updated on-line. These means are combined to define complex local geometric properties, e.g., to radii and center points of spherical regions. Using means of local scores, planar, cylindrical, and spherical segments are detected and extended robustly with region growing. For the on-line computation of the means we use so-called accumulated means. They allow for on-line insertion and removal of values and merging of means. Our results show that this approach can be performed on-line and is robust to noise. We demonstrate that our method reconstructs spherical, cylindrical, and planar segments on real scan data containing typical errors caused by hand-held laser scanners.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Agin, G., Binford, T.: Computer description of curved objects. IEEE Trans. Comput. C–25(4), 439–449 (1976)
Benkő, P., Martin, R.R., Várady, T.: Algorithms for reverse engineering boundary representation models. Comput. Aided Des. 33(11), 839–851 (2001)
Benkő, P., Várady, T.: Direct segmentation of smooth, multiple point regions. In: Geometric Modeling and Processing, pp. 169–178. IEEE (2002)
Biegelbauer, G., Vincze, M.: Efficient 3D object detection by fitting superquadrics to range image data for robot’s object manipulation. In: International Conference on Robotics and Automation, pp. 1086–1091. IEEE (2007)
Bodenmüller, T., Hirzinger, G.: Online surface reconstruction from unorganized 3d-points for the DLR hand-guided scanner system. In: 2nd Symposium on 3D Data Processing, Visualization and Transmission, pp. 285–292 (2004)
Boesch, J., Pajarola, R.: Flexible configurable stream processing of point data. In: WSCG 2009, pp. 49–56 (2009)
do Carmo, M.P.: Differential Geometry of Curves and Surfaces. Pearson, New York (1976)
Chan, T., Golub, G., Leveque, R.: Algorithms for computing the sample variance: analysis and recommendations. Am. Stat. 37(3), 242–247 (1983)
Denker, K., Hagel, D., Raible, J., Umlauf, G., Hamann, B.: On-line reconstruction of cad geometry. In: International Conference on 3D Vision, pp. 151–158 (2013)
Denker, K., Lehner, B., Umlauf, G.: Online triangulation of laser-scan data. In: Garimella, R., (ed.) 17th International Meshing Roundtable, pp. 415–432 (2008)
Denker, K., Lehner, B., Umlauf, G.: Real-time triangulation of point streams. Eng. Comput. 27(1), 67–80 (2011)
Gronau, I., Moran, S.: Optimal implementations of upgma and other common clustering algorithms. Inf. Process. Lett. 104(6), 205–210 (2007)
Holland, P.W., Welsch, R.E.: Robust regression using iteratively reweighted least-squares. Com. Stat.: Theory Methods A6, 813–827 (1977)
Jolliffe, I.: Principal Component Analysis. Springer-Verlag, Heidelberg (2002)
Knuth, D.E.: Seminumerical Algorithms, The Art of Computer Programming, 3rd (edn.), chap. 4.2.2, vol. 2, p. 232. Addison-Wesley, Boston (1998)
Ling, R.F.: Comparison of several algorithms for computing sample means and variances. J. Am. Stat. Assoc. 69(348), 859–866 (1974)
Page, D., Sun, Y., Koschan, A., Paik, J., Abidi, M.: Normal vector voting: crease detection and curvature estimation on large, noisy meshes. Graph. Models 64, 199–229 (2002)
Pajarola, R.: Stream-processing points. In: IEEE Visualization, pp. 239–246 (2005)
Press, W., Teukolsky, S., Vetterling, W., Flannery, B.: Numerical Recipes: The Art of Scientific Computing. Cambridge University Press, Cambridge (2007)
Qt Project Hosting: Qt Documentation (2013). http://qt-project.org/doc/qt-5/containers.html#algorithmic-complexity
Razer: Hydra Motion Sensing Controller (2013). http://www.razerzone.com/gaming-controllers/razer-hydra
van Reeken, A.J.: Letters to the editor: dealing with Neely’s algorithms. Commun. ACM 11(3), 149–150 (1968)
Schnabel, R., Wahl, R., Klein, R.: Efficient RANSAC for point-cloud shape detection. Comput. Graph. Forum 26(2), 214–226 (2007)
Shamir, A.: A survey on mesh segmentation techniques. Comput. Graph. Forum 27(6), 1539–1556 (2008)
Sokal, R.R., Michener, C.D.: A statistical method for evaluating systematic relationships. Univ. Kans. Sci. Bull. 28, 1409–1438 (1958)
Vančo, M., Hamann, B., Brunnett, G.: Surface reconstruction from unorganized point data with quadrics. Comput. Graph. Forum 27(6), 1593–1606 (2008)
Várady, T.: Reverse engineering of geometric models - an introduction. Comp. Aided Des. 29(4), 255–268 (1997)
Welford, B.P.: Note on a method for calculating corrected sums of squares and products. Technometrics 4(3), 419–420 (1962)
Wu, J., Kobbelt, L.: Structure recovery via hybrid variational surface approximation. Comput. Graph. Forum 24(3), 277–284 (2005)
Yamazaki, I., Natarajan, V., Bai, Z., Hamann, B.: Segmenting point-sampled surfaces. Vis. Comput. 26(12), 1421–1433 (2010)
Zhong, S.: Efficient online spherical \(k\)-means clustering. In: Proceedings of 2005 IEEE International Joint Conference on Neural Networks, vol. 5, pp. 3180–3185 (2005)
Acknowledgments
This work was supported by DFG grant UM 26/5-1.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Denker, K., Hamann, B., Umlauf, G. (2015). On-line CAD Reconstruction with Accumulated Means of Local Geometric Properties. In: Boissonnat, JD., et al. Curves and Surfaces. Curves and Surfaces 2014. Lecture Notes in Computer Science(), vol 9213. Springer, Cham. https://doi.org/10.1007/978-3-319-22804-4_14
Download citation
DOI: https://doi.org/10.1007/978-3-319-22804-4_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-22803-7
Online ISBN: 978-3-319-22804-4
eBook Packages: Computer ScienceComputer Science (R0)