The Visual Computer

, Volume 22, Issue 8, pp 562–576 | Cite as

Snake terrestrial locomotion synthesis in 3D virtual environments

Regular Paper

Abstract

We present a method for a 3D snake model construction and terrestrial snake locomotion synthesis in 3D virtual environments using image sequences. The snake skeleton is extracted and partitioned into equal segments using a new iterative algorithm for solving the equipartition problem. This method is applied to 3D model construction and at the motion analysis stage. Concerning the snake motion, the snake orientation is controlled by a path planning method. An animation synthesis algorithm, based on a physical motion model and tracking data from image sequences, describes the snake’s velocity and skeleton shape transitions. Moreover, the proposed motion planning algorithm allows a large number of skeleton shapes, providing a general method for aperiodic motion sequences synthesis in any motion graph. Finally, the snake locomotion is adapted to the 3D local ground, while its behavior can be easily controlled by the model parameters yielding the appropriate realistic animations.

Keywords

Snake motion modeling Graph exploration Snake animation 

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References

  1. 1.
    Albrecht, I., Haber, J., Seidel, H.: Construction and animation of anatomically based human hands models. In: SIGGRAPH (2003)Google Scholar
  2. 2.
    Barbier, A., Galin, E., Akkouche, S.: A framework for modeling, animating, and morphing textured implicit models. Graphical Models 67(6), 166–188 (2005)CrossRefGoogle Scholar
  3. 3.
    Batalin, M.A., Sukhatme, G.S.: Efficient exploration without localization. In: Int. Conference on Robotics and Automation, Taipei, Taiwan, pp. 2714–2719 (2003)Google Scholar
  4. 4.
    Chernousko, F.: Modelling of snake-like locomotion. Appl. Math. Comput. 164(2), 415–434 (2005)MATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Dontchena, M., Yngve, G., Popovic, Z.: Layered acting for character animation. In: Proc. IEEE International Conference on Computer Vision, pp. 409–416 (2003)Google Scholar
  6. 6.
    Favreau, L., Reveret, L., Depraz, C., Cani, M.: Animal gaits from video. In: SIGGRAPH, Grenoble, France (2004)Google Scholar
  7. 7.
    Glardon, P., Boulic, R., Thalmann, D.: Dynamic obstacle avoidance for real-time character animation. Visual Comput. 22(6), 399–414 (2006)CrossRefGoogle Scholar
  8. 8.
    Gray, J.: Animal Locomotion. Norton, London (1968)Google Scholar
  9. 9.
    Ijspeert, A.: Design of artificial neural oscillatory circuits for the control of lamprey- and salamander-like locomotion using evolutionary algorithms. Ph.D. Thesis, Univ. of Edinburgh (1998)Google Scholar
  10. 10.
    Jayne, B.C.: Kinematics of terrestrial snake locomotion. Copeia 4, 915–927 (1986)CrossRefGoogle Scholar
  11. 11.
    Johnson, M.: Exploiting quaternions to support expressive interactive character motion. Ph.D. Thesis, Massachusetts Institute of Technology (2003)Google Scholar
  12. 12.
    Kavraki, L., LaValle, S., Yakey, J.: A probabilistic roadmap approach for systems with closed kinematic chains. In: Proc. of the IEEE Int. Conf. on Robotics and Automation, pp. 1671–1677 (1999)Google Scholar
  13. 13.
    Kavraki, L., Svestka, P., Latombe, J., Overmars, M.: Probabilistic roadmaps for path planning in high dimensional configuration spaces. IEEE Trans. Robotics Auto. 12(4), 566–580 (1996)CrossRefGoogle Scholar
  14. 14.
    Kim, H., Sohn, K.: 3d reconstruction from stereo images for interactions between real and virtual objects. Signal Processing: Image Commun. 20, 61–75 (2005)MATHCrossRefMathSciNetGoogle Scholar
  15. 15.
    Kovar, L., Gleicher, M., Pighin, F.: Motion graphs. In: SIGGRAPH (2002)Google Scholar
  16. 16.
    Miller, G.: The motion dynamics of snakes and worms. Computer Graphics 22(4), 169–178 (1988)CrossRefGoogle Scholar
  17. 17.
    Moon, B.R., Gans, C.: Kinematics, muscular activity and propulsion in gopher snakes. J. Experiment. Biol. 201, 2669–2684 (1998)Google Scholar
  18. 18.
    Nougaret, J., Arnaldi, B., Multon, F.: Coarse-to-fine design of feedback controllers for dynamic locomotion. Visual Comput. 13, 435–455 (1997)CrossRefGoogle Scholar
  19. 19.
    Panagiotakis, C., Georgakopoulos, G., Tziritas, G.: The curve equipartition problem. Computational Geometry (submitted, 2005)Google Scholar
  20. 20.
    Panagiotakis, C., Georgakopoulos, G., Tziritas, G.: On the curve equipartition problem: a brief exposition of basic issues. In: European Workshop on Computational Geometry, Delphi, Greece (2006)Google Scholar
  21. 21.
    Panagiotakis, C., Tziritas, G.: Construction of animal models and motion synthesis in 3D virtual environments using image sequences. In: Proc. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, Thessaloniki, Greece (2004)Google Scholar
  22. 22.
    Panagiotakis, C., Tziritas, G.: Recognition and tracking of the members of a moving human body. In: Proc. of the 3rd International Workshop on Articulated Motion and Deformable Objects, pp. 86–98. Springer, Berlin Heidelberg New York (2004)Google Scholar
  23. 23.
    Ramanan, D., Forsyth, D.: Using temporal coherence to build models of animals. In: Proc. IEEE International Conference on Computer Vision, pp. 338–345 (2003)Google Scholar
  24. 24.
    Saito, M., Fukaya, M., Iwasaki, T.: Modeling, analysis, and synthesis of serpentine locomotion with a multilink robotic snake. IEEE Control Systems Magazine 22(1), 64–81 (2002)CrossRefGoogle Scholar
  25. 25.
    Sifakis, E., Grinias, I., Tziritas, G.: Video segmentation using fast marching and region growing algorithms. EURASIP J. Appl. Signal Process. 2002(4), 379–388 (2002)MATHCrossRefGoogle Scholar
  26. 26.
    Sminchisescu, C., Triggs, B.: Building roadmaps of minima and transitions in visual models. Int. J. Comput. Vision 61(1), 81–101 (2005)CrossRefGoogle Scholar
  27. 27.
    Tsakiris, D., Sfakiotakis, M., Menciassi, A., LaSpina, G., Dario, P.: Polychaete-like undulatory robotic locomotion. In: Proc. IEEE International Conference Robotics and Automation, Barcelona, Spain, pp. 3029–3034 (2005)Google Scholar
  28. 28.
    Watts, D.J., Strogatz, S.H.: Collective dynamics of small-world networks. Nature 393, 340–442 (1998)CrossRefGoogle Scholar
  29. 29.
    Wilhelms, J., Gelder, A.V.: Combining vision and computer graphics for video motion capture. Visual Comput. 19(6), 360–376 (2003)CrossRefGoogle Scholar
  30. 30.
    Wu, J., Popovic, Z.: Realistic modeling of bird flight animations. In: SIGGRAPH, pp. 888–895 (2003)Google Scholar
  31. 31.
    Yang, L., J., Singh, K.: Layered dynamic control for interactive character swimming. In: SIGGRAPH, Grenoble, France, pp. 37–49 (2004)Google Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.Computer Science DepartmentUniversity of CreteHeraklionGreece

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