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Interactive Evolution for Designing Motion Variants

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Computational Intelligence (IJCCI 2009)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 343))

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Abstract

We present an intuitive method for novice users to interactively design custom populations of stylized, heterogeneous motion, from one input motion. The user sets up lattice deformers which are used by a genetic algorithm to manipulate the animation channels of the input motion and create new motion variants. Our interactive evolutionary design environment allows the user to traverse the available space of possibilities, presents the user with populations of motion, and gradually converges to a satisfactory set of solutions. Each generated motion can undergo a filtering process subject to user-specified, high-level metrics to produce a result crafted to fit the designer’s interest. We demonstrate application to both character animation and particle systems.

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References

  1. Sims, K.: Evolving 3d morphology and behavior by competition. Artificial Life 1(4), 353–372 (1994)

    Article  Google Scholar 

  2. Gritz, L., Hahn, J.K.: Genetic programming for articulated figure motion. Journal of Visualization and Computer Animation 6, 129–142 (1995)

    Article  Google Scholar 

  3. Sims, K.: Interactive evolution of equations for procedural models. The Visual Computer 9(8), 466–476 (1993)

    Article  Google Scholar 

  4. Lim, I.S., Thalmann, D.: Tournament selection for browsing temporal signals. In: Proceedings of Symposium on Applied Computing 2000, pp. 570–573. ACM, New York (2000)

    Chapter  Google Scholar 

  5. Lim, I.S., Thalmann, D.: Pro-actively interactive evolution for computer animation. In: Proceedings of Computer Animation and Simulation 1999, pp. 45–52 (1999)

    Google Scholar 

  6. Ventrella, J.: Disney meets darwin-the evolution of funny animated figures. Computer Animation (1995)

    Google Scholar 

  7. Marks, J., et al.: Design galleries: a general approach to setting parameters for computer graphics and animation. In: Proceedings of SIGGRAPH 1997, pp. 389–400. ACM Press/Addison-Wesley Publishing Co., New York (1997)

    Google Scholar 

  8. Lewis, M.: Evolutionary visual art and design. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music, pp. 3–37. Springer, Heidelberg (2007)

    Google Scholar 

  9. Amaya, K., Bruderlin, A., Calvert, T.: Emotion from motion. In: Graphics Interface 1996, pp. 222–229 (1996)

    Google Scholar 

  10. Sung, M.: Continuous motion graph for crowd simulation. In: Hui, K.-c., Pan, Z., Chung, R.C.-k., Wang, C.C.L., Jin, X., Göbel, S., Li, E.C.-L. (eds.) EDUTAINMENT 2007. LNCS, vol. 4469, pp. 202–213. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  11. Chi, D., Costa, M., Zhao, L., Badler, N.: The emote model for effort and shape. In: Proceedings of SIGGRAPH 2000, pp. 173–182. ACM Press/Addison-Wesley Publishing Co., New York (2000)

    Google Scholar 

  12. Neff, M., Fiume, E.: Aer: aesthetic exploration and refinement for expressive character animation. In: Proceedings of SCA 2005, pp. 161–170. ACM Press, New York (2005)

    Google Scholar 

  13. Wang, J., Drucker, S.M., Agrawala, M., Cohen, M.F.: The cartoon animation filter. ACM Transactions on Graphics 25(3), 1169–1173 (2006)

    Article  Google Scholar 

  14. Gleicher, M.: Comparing constraint-based motion editing methods. Graphical Models 63(2), 107–134 (2001)

    Article  MATH  Google Scholar 

  15. Kwon, T., Lee, K.H., Lee, J., Takahashi, S.: Group motion editing. In: Proceedings of SIGGRAPH 2008, pp. 1–8. ACM, New York (2008)

    Google Scholar 

  16. Treuille, A., Cooper, S., Popovic, Z.: Continuum crowds. ACM Transactions on Graphics 25(3), 1160–1168 (2006)

    Article  Google Scholar 

  17. Li, T.Y., Wang, C.C.: An evolutionary approach to crowd simulation. Autonomous Robots and Agents, 119–126 (2007)

    Google Scholar 

  18. Sung, M., Kovar, L., Gleicher, M.: Fast and accurate goal-directed motion synthesis for crowds. In: Proceedings of Symposium on Computer Animation 2005, pp. 291–300. ACM Press, New York (2005)

    Google Scholar 

  19. Musse, S.R., Thalmann, D.: Hierarchical model for real time simulation of virtual human crowds. IEEE Transactions on Visualization and Computer Graphics 7(2), 152–164 (2001)

    Article  Google Scholar 

  20. Massive Software: Massive prime (2009), www.massivesoftware.com/prime

  21. Sims, K.: Artificial evolution for computer graphics. In: Proceedings of SIGGRAPH 1991, vol. 25, pp. 319–328. ACM Press, New York (1991)

    Google Scholar 

  22. Hastings, E.J., Guha, R.K., Stanley, K.O.: Neat particles: Design, representation, and animation of particle system effects. In: IEEE CIG 2007 (2007)

    Google Scholar 

  23. Hastings, E.J., Guha, R.K., Stanley, K.O.: Interactive evolution of particle systems for computer graphics and animation. Trans. Evol. Comp. 13(2), 418–432 (2009)

    Article  Google Scholar 

  24. Bezirtzis, B.G., Lewis, M., Christeson, C.: Interactive evolution for industrial design. In: C&C 2007:Proceedings of the 6th ACM SIGCHI Conference on Creativity & Cognition, pp. 183–192. ACM, New York (2007)

    Google Scholar 

  25. Tufte, E.R.: Envisioning Information. Graphics Press (May 1990)

    Google Scholar 

  26. Sederberg, T.W., Parry, S.R.: Free-form deformation of solid geometric models. In: Proceedings of SIGGRAPH 1986, vol. 20(4), pp. 151–160 (1986)

    Google Scholar 

  27. Tak, S., Song, O.Y., Ko, H.S.: Spacetime sweeping: An interactive dynamic constraints solver. In: Proceedings of Computer Animation 2002, pp. 261–271. IEEE Computer Society, Washington, DC (2002)

    Google Scholar 

  28. Müller, A.: Collision avoiding continuation method for the inverse kinematics of redundant manipulators. In: Proceedings of Robotics and Automation 2004, vol. 2, pp. 1593–1598 (2004)

    Google Scholar 

  29. Mcdonnell, R., Larkin, M., Dobbyn, S., Collins, S., O’Sullivan, C.: Clone attack! perception of crowd variety. In: Proceedings of SIGGRAPH 2008, vol. 27, pp. 1–8. ACM Press, New York (2008)

    Google Scholar 

  30. Kovar, L., Gleicher, M., Pighin, F.: Motion graphs. In: Proceedings of SIGGRAPH 2002, vol. 21, pp. 473–482. ACM Press, New York (2002)

    Google Scholar 

  31. Ko, H., Badler, N.I.: Animating human locomotion with inverse dynamics. IEEE Computer Graphics and Applications 16(2), 50–59 (1996)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Computer Science & Engineering, The Ohio State University, 2015 Neil Ave, Columbus, OH, U.S.A.

    Jonathan Eisenmann & Bryan Cline

  2. Advanced Computing Center for the Arts & Design, The Ohio State University, 1224 Kinnear Rd, Columbus, OH, U.S.A.

    Matthew Lewis

Authors
  1. Jonathan Eisenmann
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  2. Matthew Lewis
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  3. Bryan Cline
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Editor information

Editors and Affiliations

  1. Images, Signals and Intelligence Systems Laboratory, University PARIS-EST Creteil (UPEC), LISSI EA 3956, Paris 12, France

    Kurosh Madani

  2. Departamento de Engenharia Informatica Polo II - Pinhal de Marrocos, University of Coimbra, 3030, Coimbra, Portugal

    António Dourado Correia

  3. Evolutionary Systems and Biomedical Engineering Lab, Instituto Superior Tecnico IST Systems and Robotics Institute, Av. Rovisco Pais, 1049-001, Lisboa, Portugal

    Agostinho Rosa

  4. Polytechnic Institute of Setúbal / INSTICC, 2910-595, Setubal, Portugal

    Joaquim Filipe

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© 2011 Springer-Verlag GmbH Berlin Heidelberg

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Eisenmann, J., Lewis, M., Cline, B. (2011). Interactive Evolution for Designing Motion Variants. In: Madani, K., Correia, A.D., Rosa, A., Filipe, J. (eds) Computational Intelligence. IJCCI 2009. Studies in Computational Intelligence, vol 343. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20206-3_9

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  • DOI: https://doi.org/10.1007/978-3-642-20206-3_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20205-6

  • Online ISBN: 978-3-642-20206-3

  • eBook Packages: EngineeringEngineering (R0)

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