Advertisement

Multimedia Tools and Applications

, Volume 73, Issue 3, pp 1709–1722 | Cite as

An improved contraction-based method for mesh skeleton extraction

  • Liyang Yu
  • Qi HanEmail author
  • Xiamu Niu
Article

Abstract

Contraction-based skeleton extraction methods have the feature that during skeleton extraction process, the correspondence between skeleton and mesh regions can be obtained, which makes this class of algorithm attractive. Besides, among all mesh skeleton extraction methods, contraction-based methods possesses the merits of robustness to noise, rotation invariant and no requirement on additional boundary conditions. However, contraction-based methods still suffer some flaws such as not promising homotopy or centeredness, or not capable of processing non-closed meshes, etc. In this paper, an improved contraction-based skeleton extraction method is proposed which covers the failure of existing methods at non-closed part of a model and increases the rationality of the centeredness correction of the skeleton: First, non-closed models are virtually closed by a preprocessing stage such that models with boundaries can be contracted in the same way as the closed ones. Second, to improve the centeredness of the skeleton, we present a simpler and more effective one-ring area sequence weighting scheme by which the displacements measuring the shift of skeleton nodes can be calculated. Experimental results show the effectiveness of our work.

Keywords

Skeleton extraction Geometry contraction Centeredness Non-closed mesh 

Notes

Acknowledgements

We would like to thank all anonymous reviewers for their helpful comments and suggestions.This work is supported by the National Natural Science Foundation of China (61100187), the Fundamental Research Funds for the Central Universities (Grant No. HIT. NSRIF. 2010046) and the China Postdoctoral Science Foundation (2011M500666).

References

  1. 1.
    Arcelli C, di Baja GS, Serino L (2011) Distance-driven skeletonization in voxel images. IEEE Trans Pattern Anal Mach Intell 33(4):709–720. doi: 10.1109/TPAMI.2010.140 CrossRefGoogle Scholar
  2. 2.
    Attene M, Biasotti S, Spagnuolo M (2003) Shape understanding by contour-driven retiling. Vis Comput 19:127–138. doi: 10.1007/s00371-002-0182-y zbMATHGoogle Scholar
  3. 3.
    Au OKC, Tai CL, Chu HK, Cohen-Or D, Lee TY (2008) Skeleton extraction by mesh contraction. ACM Trans Graph 27(3). doi: 10.1145/1360612.1360643 (ACM SIGGRAPH Conference 2008, Singapore, Singapore, 11–15 Aug 2008)Google Scholar
  4. 4.
    Aujay G, Hetroy F, Lazarus F, Depraz C (2007) Harmonic skeleton for realistic character animation. In: Metaxas D, Popovic J (eds) Symposium on computer animation 2007: ACM SIGGRAPH/Eurographics symposium proceedings. ACM SIGGRAPH; Eurog Assoc. Symposium on computer animation. San Diego, CA, 3–4 Aug 2007, pp 151–160Google Scholar
  5. 5.
    Cao J, Tagliasacchi A, Olson M, Zhang H, Su Z (2010) Point cloud skeletons via Laplacian based contraction. In: Pernot JP, Rossignac J, Spagnuolo M, Falcidieno B, Veron P (eds) Proceedings of the Shape Modeling International (SMI 2010). Shape Modeling International (SMI 2010), 21–23 June 2010. Aix-en-Provence, France, pp 187–97Google Scholar
  6. 6.
    Cgal Computational Geometry Algorithms Library. (1997)http://www.cgal.org. Accessed 19 Oct 2011
  7. 7.
    Cornea ND (2007) Curve-skeletons: properties, computation and applications. Ph.D. thesis, Rutgers, The State University of New JerseyGoogle Scholar
  8. 8.
    Cornea N, Silver D, Yuan X, Balasubramanian R (2005) Computing hierarchical curve-skeletons of 3D objects. Vis Comput 21(11):945–955. doi: 10.1007/s00371-005-0308-0 CrossRefGoogle Scholar
  9. 9.
    Cornea ND, Silver D, Min P (2007) Curve-skeleton properties, applications, and algorithms. IEEE Trans Vis Comput Graph 13(3):530–548. doi: 10.1109/TVCG.2007.1002 CrossRefGoogle Scholar
  10. 10.
    Dey TK, Sun J (2006) Defining and computing curve-skeletons with medial geodesic function. In: Geometry processing, Eurographics, SGP. Eurographics Association, Aire-la-Ville, pp 143–152Google Scholar
  11. 11.
    Hilaga M, Shinagawa Y, Kohmura T, Kunii T (2001) Topology matching for fully automatic similarity estimation of 3D shapes. In: SIGGRAPH 2001 conference proceedings. Computer graphics. ACM SIGGRAPH. SIGGRAPH 2001, Los Angeles, CA, 12–17 Aug 2001, pp 203–212Google Scholar
  12. 12.
    Ma C-M, Wan S-Y, Lee J-D (2002) Three-dimensional topology preserving reduction on the 4-subfields. IEEE Trans Pattern Anal Mach Intell 24:1594–605CrossRefGoogle Scholar
  13. 13.
    Ma W-C, Wu F-C, Ouhyoung M (2003) Skeleton extraction of 3D objects with radial basis functions. In: Kim M-S (ed) Proceedings. Shape modeling international 2003, 12–15 May 2003. Seoul, South Korea, pp 207–215Google Scholar
  14. 14.
    Ogniewicz R, Ilg M (1992) Voronoi skeletons: theory and applications. In: Proceedings. 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.92CH3168-2). IEEE, 15–18 June 1992, Champaign, IL, USA, pp 63–69Google Scholar
  15. 15.
    Palagyi K, Kuba A (1999) A parallel 3D 12-subiteration thinning algorithm. GMIP 61(4):199–221. doi: 10.1006/gmip.1999.0498 Google Scholar
  16. 16.
    Pantuwong N, Sugimoto M (2010) Skeleton-growing: a vector-field-based 3d curve-skeleton extraction algorithm. In: ACM SIGGRAPH Asia 2010 sketches, SA ’10. ACM, New York, NY, pp 6:1–6:2.  10.1145/1899950.1899956 CrossRefGoogle Scholar
  17. 17.
    Shilane P, Min P, Kazhdan M, Funkhouser T (2004) The princeton shape benchmark. In: Shape modeling applications, 2004. Proceedings. IEEE, pp 167–178Google Scholar
  18. 18.
    Wang Y-S, Lee T-Y (2008) Curve-skeleton extraction using iterative least squares optimization. IEEE Trans Vis Comput Graph 14:926–36CrossRefGoogle Scholar
  19. 19.
    Willcocks C, Li F (2012) Feature-varying skeletonization. Vis Comput 28:775–785. doi: 10.1007/s00371-012-0688-x CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyHarbin Institute of TechnologyHabinChina
  2. 2.Department of Computer Science and TechnologyMudanjiang Normal UniversityMudanjiang CityChina

Personalised recommendations