International Journal of CAD/CAM

Society for Computational Design and Engineering (한국CDE학회)
권호 표지

A Nonparametric Approach for Noisy Point Data Preprocessing

  • Published : 2010.04.01
Download PDF
⟨ Previous Next ⟩

Abstract

3D point data acquired from laser scan or stereo vision can be quite noisy. A preprocessing step is often needed before a surface reconstruction algorithm can be applied. In this paper, we propose a nonparametric approach for noisy point data preprocessing. In particular, we proposed an anisotropic kernel based nonparametric density estimation method for outlier removal, and a hill-climbing line search approach for projecting data points onto the real surface boundary. Our approach is simple, robust and efficient. We demonstrate our method on both real and synthetic point datasets.

Keywords

References

  1. Alexa, M., Behr, J., Cohen-Or, D., Fleishman, S., Levin, D., Silva, C.T., Computing and rendering point set surfaces. IEEE Transactions on Visualization and Computer Graphics 9, 1, 3–15. 2003.
  2. Amenta, N and Bern, M, Surface reconstruction by voronoi filtering, Discrete and Comput. Geometry, vol. 22, pp. 481-504, 1999. https://doi.org/10.1007/PL00009475
  3. Amenta, N., Bern, M., and Eppstein, D., The crust and the -skeleton: Combinational curve reconstruction, 14th ACM Symposium on Computational Geometry, 1998.
  4. Amenta, N., Bern, M., and Kamvysselis, M., A new voronoi-based surface reconstruction algorithm, in SIGGRAPH '98: Proceedings of the 25th annual conference on Computer graphics and interactive techniques, (New York, NY, USA), pp. 415-421, ACM Press, 1998.
  5. Amenta, N., Kil, Y. J., Defining point-set surfaces. ACM Trans. Graph. 23(3): 264-270 (2004) https://doi.org/10.1145/1015706.1015713
  6. Bajaj, C. L., Bernardini, F., and Xu, G., Automatic reconstruction of surfaces and scalar fields from 3d scans, in SIGGRAPH '95: Proceedings of the 22nd annual conference on Computer graphics and interactive techniques, (New York, NY, USA), pp. 109-118, ACM Press, 1995.
  7. Boissonnat, J. D., Geometric structures for three dimensional shape reconstruction, ACM Trans. Graphics 3, pp. 266-286, 1984. https://doi.org/10.1145/357346.357349
  8. Carr, J. C., Beatson, R. K., Cherrie, J. B., Mitchell, T. J., Fright, W. R., McCallum, B. C., and Evans, T. R., Reconstruction and representation of 3d objects with radial basis functions, in SIGGRAPH '01: Proceedings of the 28th annual conference on Computer graphics and interactive techniques, (New York, NY, USA), pp. 67-76, ACM Press, 2001.
  9. Curless, B., and Levoy, M., A volumetric method for building complex models from range images, in SIGGRAPH '96: Proceedings of the 23rd annual conference on Computer graphics and interactive techniques, (New York, NY, USA), pp. 303-312, ACM Press, 1996.
  10. Duda, R. O., Hart, P. E., Stork, D. G., Pattern Classification, October 2000, Wiley-Interscience; 2 edition.
  11. Edelsbrunner, H., Shape reconstruction with delaunay complex, in LATIN '98: Proceedings of the Third Latin American Symposium on Theoretical Informatics, (London, UK), pp. 119-132, Springer-Verlag, 1998.
  12. Hoppe, H., DeRose, T., Duchamp, T., McDonald, J., and Stuetzle, W., Surface reconstruction from unorganized points, in SIGGRAPH '92: Proceedings of the 19th annual conference on Computer graphics and interactive techniques, (New York, NY, USA), pp. 71-78, ACM Press, 1992.
  13. Hilton, A., Stoddart, A. J., Illingworth, J., and Windeatt, T., Implicit surface-based geometric fusion, Comput. Vis. Image Underst., vol. 69, no. 3, pp. 273-291, 1998. https://doi.org/10.1006/cviu.1998.0664
  14. Levin, D., Mesh-independent surface interpolation. In Geometric Modeling for Scientific Visualization, G. Brunnett, B. Hamann, K. Mueller, and L. Linsen, Eds. Springer- Verlag, 2003.
  15. Medioni, G., Lee, M.-S., and Tang, C.-K., A computational framework for segmentation and grouping. Elsevier, 2000.
  16. Ohtake, Y., Belyaev, A., Alexa, M., Turk, G., and Seidel, H., Multi-level partition of unity implicits, ACM Trans.Graph, 2003, Pages: 463-470. https://doi.org/10.1145/882262.882293
  17. Seitz, S., Curless, B., Diebel, J., Scharstein, D., and Szeliski, R., A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms, CVPR 2006, vol. 1, pages 519-526.
  18. Whitaker, R., A level set approach to 3D reconstruction from range data, International journal of Computer Vision, 1997.
  19. Xie, H., Wang, J., Hua, J., Qin, H., Kaufman, A., Piecewise c1 continuous surface reconstruction of noisy point clouds via local implicit quadric regression. IEEE Visualization 2003, 91–98.
  20. Zhao, H., Osher, S., Merriman, B., and Kang, M., Implicit and non-parametric shape reconstruction from unorganized data using a variational level set method, Computer Vision and Image Understanding, vol. 80, pp. 295-319, 2000. https://doi.org/10.1006/cviu.2000.0875
  21. Zhao, H., Osher, S., and Fedkiw, R., Fast surface reconstruction using the level set method, in VLSM '01: Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01), (Washington, DC, USA), p. 194, IEEE Computer Society, 2001.