Abstract
Point cloud simplification has become a vital step in any point-based surface processing pipeline. This paper describes a fast and effective algorithm for point cloud simplification with feature preservation. First, feature points are extracted by thresholding curvatures; Second, for non-feature points, they are covered by distinct balls, the points in each ball are substituted by an optimized point. Thus, the simplified point cloud consists of extracted feature points and optimized points. This algorithm is able to produce coarse-to-fine models by controlling a general error level. But the error level of each ball may be adaptively adjusted according to the local curvature and density that can avoid holes generation during the simplification process. Finally, the simplified points are triangulated by Cocone algorithm for surface reconstruction. This algorithm has been applied to a set of large scanned models. Experimental results demonstrate that it can generate high-quality surface approximation with feature preservation.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Linsen, L.: Point cloud representation. CS Technical Report 2001-3. Universitat Karlsruhe, Germany (2001)
Alexa, M., Behr, J., Cohen-Or, D., et al.: Point Set Surfaces. In: Proc. 12th IEEE Visualization Conf., San Diego, USA, pp. 21–28 (2001)
Dey, T.K., Giesen, J., Hudson, J.: Decimating samples for mesh simplification. In: Proc. of 13th Canadian Conference on Computational Geometry, pp. 85–88 (2001)
Alexa, M., Behr, J., Cohen-Or, D., et al.: Computer and rendering point set surface. IEEE Transaction on Visaulization and Computer Graphics 9(1), 3–15 (2003)
Scheidegger, C., Fleishman, S., Silva, C.: Triangulating point set surfaces with bounded error. In: Eurographics Symposium on Geometry Processing, pp. 63–72 (2005)
Kalaiah, A., Varshney, A.: Modeling and rendering of points with local geometry. IEEE Trans. Vis. Comput Graphics 9(1), 30–42 (2003)
Lee, K., Woo, H., Suk, T.: Point data reduction using 3D grids. The International Journal of Advanced Manufacturing Technology 18(3), 201–210 (2001)
Miao, Y., Pajarola, R., Feng, J.: Curvature-aware adaptive re-sampling for point- sampled geometry. Computer-Aided Design 41(6), 395–403 (2009)
Boissonnat, J.D., Cazals, F.: Coarse-to-fine surface simplification with geometric guarantees. In: Proc. of EUROGRAPHICS, pp. 490–499 (2001)
Moenning, C., Dodgson, N.A.: Intrinsic point cloud simplification. In: Proc. of 14th GrahiCon (2004)
Wu, J., Kobbelt, L.P.: Optimized sub-sampling of point sets for surface splatting. In: Proc. of EUROGRAPHICS, pp. 643–652 (2000)
Pauly, M., Gross, M., Kobbelt, L.P.: Eifficient simplifiction of point-sampled surfaces. In: Proc. of IEEE Visualization, pp. 163–170 (2002)
Yu, Z., Wong, H., Peng, H., et al.: An adaptive simplification method for 3D point-based models. Computer-Aided Design 42(7), 598–612 (2010)
Shi, B., Liang, J., Liu, Q.: Adaptive simplification of point cloud using k-means clustering. Computer-Aided Design 43(8), 910–922 (2011)
Song, H., Feng, H.: A global clustering approach to point cloud simplification with a specified data reduction ratio. Computer-Aided Design 40(3), 281–292 (2008)
Garland, M., Heckbert, P.: Surface simplification using quadric error metrics. In: Proc. of SIGGRAPH, pp. 209–216 (1997)
Wang, R., Hang, S., Ye, X.: A novel simplification algorithm for point-sampled surfaces. In: International Conference on Multimedia and Ubiquitous Engineering, pp. 573–578 (2007)
Lee, P., Jong, B.: Point-based Simplification Algorithm. WSEAS Transactions on Computer Research 3(1), 61–66 (2008)
Jong, B., Lee, P.: Hierarchical Point Simplification Using Coplanar Criterion. In: Tseng 2006 IEEE Region 10 Conference, pp. 1–4 (2006)
Ohtake, Y., Belyaev, A., Seidel, H.-P.: An integration approach to meshing scattered point data. In: ACM Symposium on Solid and Physical Modeling, pp. 61–69 (2005)
Dey, T.K., Goswami, S.: Tight Cocone: a water tight surface reconstruction reconstructor. In: Proc. of 8th ACM Sympos. Solid Modeling Appl., pp. 127–134 (2003)
Tagliasacchi, A., Zhang, H., Cohen-Or, D.: Curve skeleton extraction from incomplete point cloud. ACM Transactions on Graphics 28(3), 1–9 (2009)
Nehab, D., Rusinkiewicz, S., Davis, J., et al.: Efficiently combining positions and normals for precise 3D geometry. ACM Transactions on Graphics 25(3), 560–568 (2005)
Hoppe, H., DeRose, T., Duchamp, T., et al.: Surface reconstruction from unorganized points. In: Proc. of SIGGRAPH, pp. 71–79 (1992)
Wu, J., Wei, M., Li, Y., et al.: Scale-adaptive surface modeling of vascuar structures. BioMedical Engineering Online 9, 75 (2010)
Koenderink, J.: What does the occluding contour tell us about solid shape? Perception 13, 321–330 (1984)
Gooch, B., Sloan, P.J., Gooch, A., et al.: Interactive technical illustraction. In: Proc. ACM Symposium on 3D Interactive Graphics, pp. 31–38 (1999)
Hertzmann, A., Zorin, D.: Illustrating smooth surfaces. In: Proc. of SIGGRAPH, pp. 517–526 (2000)
Heckbert, P.S., Garland, M.: Optimal triangulation and quadric-based surface simplification. Computational Geometry: Theroy and Application 14(1-3), 49–65 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, Y., Wei, M., Wu, J., Pang, M. (2012). Error-Controllable Simplification of Point Cloud. In: Gavrilova, M.L., Tan, C.J.K. (eds) Transactions on Computational Science XVI. Lecture Notes in Computer Science, vol 7380. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32663-9_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-32663-9_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32662-2
Online ISBN: 978-3-642-32663-9
eBook Packages: Computer ScienceComputer Science (R0)