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Strategies for Part-Based Shape Analysis Using Skeletons

  • Wooi-Boon Goh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4291)

Abstract

Skeletons are often used as a framework for part-based shape analysis. This paper describes some useful strategies that can be employed to improve the performance of such shape matching algorithms. Four key strategies are proposed. The first is to incorporate ligature-sensitive information into the part decomposition and shape matching processes. The second is to treat part decomposition as a dynamic process in which the selection of the final decomposition of a shape is deferred until the shape matching stage. The third is the need to combine both local and global measures when computing shape dissimilarity. Finally, curvature error between skeletal segments must be weighted by the limb-width profile along the skeleton. Experimental results show that the incorporation of these strategies significantly improves the retrieval accuracy when applied to LEMS’s 99 and 216 silhouette database [10].

Keywords

Part Decomposition Shape Match Global Distance Skeletal Segment Query Shape 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    August, J., Siddiqi, K.S., Zucker, S.W.: Ligature Instabilities in the Perceptual Organization of Shape. In: Proc. of the Conf. on Computer Vision and Pattern Recognition, vol. 2, pp. 42–48 (1999)Google Scholar
  2. 2.
    di Baja, G.S., Thiel, E. (3,4)-weighted Skeleton Decomposition for Pattern Representation and Description. Pattern Recognition 27(8), 1039–1049 (1994)CrossRefGoogle Scholar
  3. 3.
    Belongie, S., Malik, J., Puzicha, J.: Shape Matching and Object Recognition using Shape Contexts. IEEE Trans. on Patt. Analysis and Machine Intelligence 24(24), 509–522 (2002)CrossRefGoogle Scholar
  4. 4.
    Geiger, D., Liu, T.L., Kohn, R.V.: Representation of Self-Similarity of Shapes. IEEE Trans. on Pattern Analysis and Machine Intelligence 25(1), 86–99 (2003)CrossRefGoogle Scholar
  5. 5.
    Goh, W.B., Chan, K.Y.: Structural and Textural Skeletons for Noisy Shapes. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds.) ISVC 2005. LNCS, vol. 3804, pp. 454–461. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  6. 6.
    Goh, W.B., Chan, K.Y.: Part-based Shape Recognition using Gradient Vector Field Histograms. In: Computer Analysis of Images and Pattern. LNCS, vol. 2756, pp. 402–409. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  7. 7.
    Goh, W.B.: Shape Analysis using Multiresolution Gradient Vector Field. Ph.D. Thesis, Nanyang Technological University, Singapore (2005)Google Scholar
  8. 8.
    Katz, R.A., Pizer, S.M.: Untangling the Blum Medial Axis Transform. International Journal of Computer Vision 5(2/3), 139–153 (2003)CrossRefGoogle Scholar
  9. 9.
    Kimia, B.B.: On the role of medial geometry in human vision. J. of Physiology (to appear) see, http://www.lems.brown.edu/vision/publications/Kimia’s_Publication/Journal/journals.htm
  10. 10.
  11. 11.
    Rom, H., Medioni, G.: Hierarchical Decomposition and Axial Shape Description. IEEE Trans. on Pattern Analysis and Machine Intelligence 15(10), 973–981 (1993)CrossRefGoogle Scholar
  12. 12.
    Sebastian, T.B., Klein, P.N., Kimia, B.B.: Recognition of Shapes by Editing Shock Graphs. IEEE Trans. on Pattern Analysis and Machine Intelligence 26(5), 550–571 (2004)CrossRefGoogle Scholar
  13. 13.
    Siddiqi, K.S., Shokoufandeh, A., Dickinson, S., Zucker, S.S.: Shock Graphs and Shape Matching. International Journal of Computer Vision 35(1), 13–32 (1999)CrossRefGoogle Scholar
  14. 14.
    Torsello, A., Hancock, E.R.: A Skeletal Measure of 2D Shape Similarity. Computer Vision and Image Understanding 95, 1–29 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wooi-Boon Goh
    • 1
  1. 1.School of Computer EngineeringNanyang Technological UniversitySingapore

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