Modeling of Elastic Articulated Objects and Its Parameters Determination from Image Contours

  • Hailang Pan
  • Yuncai Liu
  • Lei Shi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)


This paper presents a new method of elastic articulated objects (human bodies) modeling based on a new conic curve. The model includes 3D object deformable curves which can represent the deformation of human occluding contours. The deformation of human occluding contour can be represented by adjusting only four deformation parameters for each limb. Then, the 3D deformation parameters are determined by corresponding 2D contours from a sequences of stereo images. The algorithm presented in this paper includes deformable conic curve parameters determination and the plane, 3D conic curve lying on, parameter determination.


Deformation Parameter Parameter Determination Human Skeleton Nonrigid Motion Conic Curve 
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.


  1. 1.
    Aggarwal, J.K., Cai, Q., Liao, W.: Articulated and elastic non-rigid motion: a review. In: Proc. IEEE Workshop On Motion of Non-rigid and Articulated Objects, pp. 2–14 (1994)Google Scholar
  2. 2.
    Nahas, M., Huitric, H., Saintourens, M.: Animation of a B-Spline Figure. Visual Computer (1988)Google Scholar
  3. 3.
    Petland, A., Horowitz, B.: Recovery of Nonrigid motion and structure. IEEE Transaction on PAMI 13(7), 730–742 (1991)Google Scholar
  4. 4.
    Min, K.-H., Baek, S.-M., Lee, G.A., Choi, H., Park, C.-M.: Anatomically-based modeling and animation of human upper limbs. In: Proceedings of International Conference on Human Modeling and Animation (2000)Google Scholar
  5. 5.
    Plankers, R., Fua, P.: Articulated Soft Objects for Multiview Shape and Motion Capture. IEEE Transaction on PAMI 25(9), 1182–1187 (2003)Google Scholar
  6. 6.
    Sminchisescu, C.: Estimation Algorithms for Ambiguous Visual Models, Doctoral Thesis, INRIA (July 2002)Google Scholar
  7. 7.
    D’Apuzzo, N., Plänkers, R., Gruen, A., Fua, F., Thalmann, D.: Modelling Human Bodies from Video Sequences. In: Proc. Electronic Imaging 1999, San Jose, California (January 1999)Google Scholar
  8. 8.
    Jain, R.C., Kasturi, R., Schunk, B.: Machine Vision. McGraw-Hill Inc., New York (1995)Google Scholar
  9. 9.
    Songde, M.A.: Conics-Based Stereo, Motion Estimation, and Pose Determination. Intern. J. Computer Vision 10(1) (1993)Google Scholar
  10. 10.
    Zhang, X., Liu, Y., Huang, T.S.: Articulated Joint Estimation from Motion Using Two Monocular Images. Pattern Recognition Letters 25(10), 1097–1106 (2004)CrossRefGoogle Scholar
  11. 11.
    Zhang, Z.: Parameter Estimation Techniques: A Tutorial with Application to Conic Fitting. Image and Vision Computing Journal (1996)Google Scholar
  12. 12.
    Zhang, X., Liu, Y., Huang, T.S.: Motion Estimation of Articulated Objects from Perspective Views. In: Perales, F.J., Hancock, E.R. (eds.) AMDO 2002. LNCS, vol. 2492, pp. 165–176. Springer, Heidelberg (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Hailang Pan
    • 1
  • Yuncai Liu
    • 1
  • Lei Shi
    • 1
  1. 1.Institute of Image Processing and Pattern RecognitionShanghai Jiao Tong UniversityP.R.China

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