Advertisement

The Effects of Noise on the Perception of Animated Human Running

  • Bobby Bodenheimer
  • Anna V. Shleyfman
  • Jessica K. Hodgins
Part of the Eurographics book series (EUROGRAPH)

Abstract

Cyclic motions such as running or walking are difficult to animate because limitations in time and technology often result in only a small number of distinct cycles being produced. These few cycles are then repeated to create an animation of the desired length. Unfortunately, the repetitiveness of the resulting motion often appears unnatural. This paper seeks to fix this problem by determining how to introduce natural-looking variability into cyclic animations of human motion. We construct a noise function based on biomechanical considerations that introduces natural-looking perturbations in a base running motion produced either by dynamic simulation or from motion capture data. We evaluate our results through human subject testing.

Keywords

Computer Graphic Joint Angle Motion Capture Output Torque Cyclic Motion 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Amaya, K., Bruderlin, A., and Calvert, T. Emotion from motion. In Graphics Interface ’96 (May 1996), W. A. Davis and R. Bartels, Eds., pp. 222–229.Google Scholar
  2. 2.
    Arutyunyan, G. H., Gurfinkel, V. S., and Mirskii, M. L. Investigation of aiming at a target. Biophysics 13 (1968), 536–538.Google Scholar
  3. 3.
    Arutyunyan, G. H., Gurfinkel, V. S., and Mirskii, M. L. Organization of movements on execution by man of an exact postural task. Biophysics 14 (1969), 1162–1167.Google Scholar
  4. 4.
    Beckwith, T. G., Marangoni, R. D., And Lienhard V, J. H. Mechanical Measurements. Addison-Wesley, Reading, Mass., 1993.Google Scholar
  5. 5.
    Box, G. E. P., Hunter, W. G., and Hunter, J. S. Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building. John Wiley, New York, 1978.MATHGoogle Scholar
  6. 6.
    Bruderlin, A., and Williams, L. Motion signal processing. In Computer Graphics (Aug. 1995), pp. 97–104. Proceedings of SIGGRAPH 95.Google Scholar
  7. 7.
    Darling, W. G., and Stephenson, M. Directional effects on variability in upper limb movements. In Variability and Motor Control, K. M. Newell and D. M. Corcos, Eds. Human Kinetics, Champaign, IL, Apr. 1993, pp. 65–88.Google Scholar
  8. 8.
    DubÉ, R. L. Natural Pattern Forms. Van Nostrand Rheinhold, New York, 1997.Google Scholar
  9. 9.
    FITTS, P. M. The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology 47 (1954), 381–391.CrossRefGoogle Scholar
  10. 10.
  11. 11.
    Hodgins, J. K., Wooten, W. L., Brogan, D. C., and O’Brien, J. F. Animating human athletics. In Computer Graphics (Aug. 1995), pp. 71–78. Proceedings of SIGGRAPH 95.Google Scholar
  12. 12.
    Jazwinski, A. H. Stochastic Processes and Filtering Theory, vol. 64 of Mathematics in Science and Engineering. Academic Press, New York, 1970.Google Scholar
  13. 13.
    Kim, K., McMillan, M., and Zelaznik, H. N. Behavioral analysis of trajectory formation: The speed-accuracy trade-off as a tool to understand strategies of movement control. In Advances in Motor Learning and Control, H. N. Zelaznik, Ed. Human Kinetics, Champaign, IL, 1996, pp. 1–12.Google Scholar
  14. 14.
    Newell, K. M., and Corcos, D. M., Eds. Variability and Motor Control. Human Kinetics Publishers, Champaign, IL, 1991.Google Scholar
  15. 15.
    Perlin, K. Real time responsive animation with personality. IEEE Transactions on Visualization and Computer Graphics 1, 1 (Mar. 1995), 5–15.CrossRefGoogle Scholar
  16. 16.
    Perlin, K., and Goldberg, A. Improv: A system for scripting interactive actors in virtual worlds. In Computer Graphics (Aug. 1996), pp. 205–216. Proceedings of SIGGRAPH 96.Google Scholar
  17. 17.
    Rose, C, Cohen, M., and Bodenheimer, B. Verbs and adverbs: Multidimensional motion interpolation. IEE Computer Graphics and Applications 18, 5 (1998), 32–40.CrossRefGoogle Scholar
  18. 18.
    Rose, C. F., Guenter, B., Bodenheimer, B., and Cohen, M. Efficient generation of motion transitions using spacetime constraints. In Computer Graphics (Aug. 1996), pp. 147–154. Proceedings of SIGGRAPH 96.Google Scholar
  19. 19.
    Schlick, C. Wave generators for computer graphics. In Graphics Gems V, A. W. Paeth, Ed. Academic Press, New York, 1995, pp. 367–374.Google Scholar
  20. 20.
    Schmidt, R. A., Zelaznik, H. N., Hawkins, B., Frank, J. S., and Quinn, J. T. Motor-output variability: A theory for the accuracy of rapid motor acts. Psychological Review 86 (1979), 415–451.CrossRefGoogle Scholar
  21. 21.
    Unuma, M., Anjyo, K., and Tekeuchi, R. Fourier principles for emotion-based human figure animation. In Computer Graphics (Aug. 1995), pp. 91–96. Proceedings of SIGGRAPH 95.Google Scholar
  22. 22.
    Witkin, A., and PopoviĆ, Z. Motion warping. In Computer Graphics (Aug. 1995), pp. 105–108. Proceedings of SIGGRAPH 95.Google Scholar
  23. 23.
    Woodworth, R. S. The accuracy of voluntary movement. Psychological Review 3 (1899), 1–114.Google Scholar
  24. 24.
    Zelaznik, H.N. Necessary and sufficient conditions for the production of linear speed-accuracy trade-offs in aimed hand movements. In Variability and Motor Control, K. M. Newell and D. M. Corcos, Eds. Human Kinetics, Champaign, IL, 1991, pp. 91–115.Google Scholar

Copyright information

© Springer-Verlag Wien 1999

Authors and Affiliations

  • Bobby Bodenheimer
    • 1
  • Anna V. Shleyfman
    • 1
  • Jessica K. Hodgins
    • 1
  1. 1.College of ComputingGeorgia Institute of TechnologyAtlantaUSA

Personalised recommendations