Planning and Synthesizing Superhero Motions

  • Katsu Yamane
  • Kwang Won Sok
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6459)


This paper presents an approach to planning and synthesizing collision-free motions of characters with extreme physical capabilities, or superheroes, using a human motion database. The framework utilizes the author’s previous work on momentum-based motion editing, where the user can scale the momentum of a motion capture sequence to make more or less dynamics motions, while maintaining the physical plausibility and original motion style. In our new planning framework, we use a motion graph that contains all possible motion transitions to list the candidate motion segments at each planning step. The planner then computes the momentum scale that should be applied to the original motion segment in order to make it collision-free. Experimental results demonstrate that the planning algorithm can plan and synthesize motions for navigating through a challenging environment, using a relatively small motion capture data set.


Planning Motion Graphs Momentum Editing Motion Capture 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Arikan, O., Forsyth, D.A.: Synthesizing Constrained Motions from Examples. ACM Transactions on Graphics 21(3), 483–490 (2002)CrossRefzbMATHGoogle Scholar
  2. 2.
    Da Silva, M., Abe, Y., Popović, J.: Interactive simulation of stylized human locomotion. ACM Transactions on Graphics 27(3), 82 (2008)CrossRefGoogle Scholar
  3. 3.
    Gleicher, M.: Retargetting Motion to New Characters. In: Proceedings of SIGGRAPH 1998, Orlando, FL, pp. 33–42 (1998)Google Scholar
  4. 4.
    Kovar, L., Gleicher, M., Pighin, F.: Motion graphs. ACM Transactions on Graphics 21(3), 473–482 (2002)CrossRefGoogle Scholar
  5. 5.
    Lee, J., Chai, J., Reitsma, P.S.A., Hodgins, J.K., Pollard, N.S.: Interactive Control of Avatars Animated With Human Motion Data. ACM Transactions on Graphics 21(3), 491–500 (2002)Google Scholar
  6. 6.
    Lee, Y., Kim, S., Lee, J.: Data-driven biped control. ACM Transactions on Graphics 29(4), 129 (2010)Google Scholar
  7. 7.
    Muico, U., Lee, Y., Popović, J., Popović, Z.: Contact-aware nonlinear control of dynamic characters. ACM Transactions on Graphics 28(3) (2009)Google Scholar
  8. 8.
    Rose, C., Cohen, M., Bodenheimer, B.: Verbs and Adverbs: Multidimentional Motion Interpolation. IEEE Computer Graphics and Applications 18(5), 32–40 (1998)CrossRefGoogle Scholar
  9. 9.
    Safonova, A., Hodgins, J.: Interpolated motion graphs with optimal search. ACM Transactions on Graphics 26(3), 106 (2007)CrossRefGoogle Scholar
  10. 10.
    Sok, K., Kim, M., Lee, J.: Simulating biped behaviors from human motion data. ACM Transactions on Graphics 26(3) (2007)Google Scholar
  11. 11.
    Sok, K., Yamane, K., Lee, J., Hodgins, J.: Editing dynamic human motions via momentum and force. In: Eurographics/ACM SIGGRAPH Symposium on Computer Animation (2010)Google Scholar
  12. 12.
    LaValle, S.M.: Planning Algorithms. Cambridge University Press, New York (2006)CrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Katsu Yamane
    • 1
    • 2
  • Kwang Won Sok
    • 2
  1. 1.Disney Research, PittsburghPittsburghUSA
  2. 2.Carnegie Mellon UniversityUSA

Personalised recommendations