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== DOI ==
 
== DOI ==
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http://dx.doi.org/10.1145/1254960.1254986
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http://link.springer.com/chapter/10.1007%2F978-3-642-20206-3_9
  
 
== Abstract ==
 
== Abstract ==
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Interactive evolutionary design (IED) has the potential to change development processes in industrial design from generating individual solutions to designing parametric models that are employed to create a vast space of possible solutions. This paper describes the current stage of a continuing interdisciplinary project between computer science and industrial design to make IED accessible for designers. The long term goal is to integrate the software into participatory design research methods, since interactive evolutionary design interfaces can be used without extensive training and skills. Everybody can use it to intuitively identify, communicate and explore appealing solutions within a large solution space. A case study is conducted to illustrate initial experiences by applying interactive evolutionary design software to the design process of a small, electric vehicle. The findings of the case study are immediately applied to further develop the software as a new design tool. The main contribution of this article is an explanation of basic techniques for designers/artists to design and shape a solution space.
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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.
  
 
== Extended Abstract ==
 
== Extended Abstract ==
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== Used References ==
 
== Used References ==
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Karl Sims, Artificial evolution for computer graphics, ACM SIGGRAPH Computer Graphics, v.25 n.4, p.319-328, July 1991  http://dl.acm.org/citation.cfm?id=122752&CFID=588525319&CFTOKEN=29804931 http://doi.acm.org/10.1145/127719.122752
+
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+
Gleicher, M.: Comparing constraint-based motion editing methods. Graphical Models 63(2), 107–134 (2001) http://dx.doi.org/10.1006/gmod.2001.0549
 +
   
 +
Kwon, T., Lee, K.H., Lee, J., Takahashi, S.: Group motion editing. In: Proceedings of SIGGRAPH 2008, pp. 1–8. ACM, New York (2008) http://dx.doi.org/10.1145/1399504.1360679
 +
   
 +
Treuille, A., Cooper, S., Popovic, Z.: Continuum crowds. ACM Transactions on Graphics 25(3), 1160–1168 (2006) http://dx.doi.org/10.1145/1141911.1142008
 +
   
 +
Li, T.Y., Wang, C.C.: An evolutionary approach to crowd simulation. Autonomous Robots and Agents, 119–126 (2007)
 +
   
 +
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)
 +
   
 +
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) http://dx.doi.org/10.1109/2945.928167
 +
   
 +
Massive Software: Massive prime (2009), www.massivesoftware.com/prime
 +
   
 +
Sims, K.: Artificial evolution for computer graphics. In: Proceedings of SIGGRAPH 1991, vol. 25, pp. 319–328. ACM Press, New York (1991) http://dx.doi.org/10.1145/122718.122752
 +
 
 +
Hastings, E.J., Guha, R.K., Stanley, K.O.: Neat particles: Design, representation, and animation of particle system effects. In: IEEE CIG 2007 (2007)
 +
   
 +
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) http://dx.doi.org/10.1109/TEVC.2008.2004261
 +
   
 +
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) http://dx.doi.org/10.1145/1254960.1254986
 +
   
 +
Tufte, E.R.: Envisioning Information. Graphics Press (May 1990)
 +
   
 +
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)
 +
   
 +
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)
 +
   
 +
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)
 +
   
 +
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) http://dx.doi.org/10.1145/1399504.1360625
 +
 
 +
Kovar, L., Gleicher, M., Pighin, F.: Motion graphs. In: Proceedings of SIGGRAPH 2002, vol. 21, pp. 473–482. ACM Press, New York (2002) http://dx.doi.org/10.1145/566570.566605
 +
   
 +
Ko, H., Badler, N.I.: Animating human locomotion with inverse dynamics. IEEE Computer Graphics and Applications 16(2), 50–59 (1996) http://dx.doi.org/10.1109/38.486680
  
  

Version vom 9. Januar 2015, 22:56 Uhr

Reference

Jonathan Eisenmann, Matthew Lewis, Bryan Cline: Interactive Evolutionary Design of Motion Variants. IJCCI 2009: 127-134.

DOI

http://link.springer.com/chapter/10.1007%2F978-3-642-20206-3_9

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.

Extended Abstract

Bibtex

Used References

Sims, K.: Evolving 3d morphology and behavior by competition. Artificial Life 1(4), 353–372 (1994) http://dx.doi.org/10.1162/artl.1994.1.4.353

Gritz, L., Hahn, J.K.: Genetic programming for articulated figure motion. Journal of Visualization and Computer Animation 6, 129–142 (1995) http://dx.doi.org/10.1002/vis.4340060303

Sims, K.: Interactive evolution of equations for procedural models. The Visual Computer 9(8), 466–476 (1993) http://dx.doi.org/10.1007/BF01888721

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) http://dx.doi.org/10.1145/338407.338499

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

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

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) http://dx.doi.org/10.1145/258734.258887

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)

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

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) http://dx.doi.org/10.1007/978-3-540-73011-8_22

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) http://dx.doi.org/10.1145/344779.352172

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)

Wang, J., Drucker, S.M., Agrawala, M., Cohen, M.F.: The cartoon animation filter. ACM Transactions on Graphics 25(3), 1169–1173 (2006) http://dx.doi.org/10.1145/1141911.1142010

Gleicher, M.: Comparing constraint-based motion editing methods. Graphical Models 63(2), 107–134 (2001) http://dx.doi.org/10.1006/gmod.2001.0549

Kwon, T., Lee, K.H., Lee, J., Takahashi, S.: Group motion editing. In: Proceedings of SIGGRAPH 2008, pp. 1–8. ACM, New York (2008) http://dx.doi.org/10.1145/1399504.1360679

Treuille, A., Cooper, S., Popovic, Z.: Continuum crowds. ACM Transactions on Graphics 25(3), 1160–1168 (2006) http://dx.doi.org/10.1145/1141911.1142008

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

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)

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) http://dx.doi.org/10.1109/2945.928167

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

Sims, K.: Artificial evolution for computer graphics. In: Proceedings of SIGGRAPH 1991, vol. 25, pp. 319–328. ACM Press, New York (1991) http://dx.doi.org/10.1145/122718.122752

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

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) http://dx.doi.org/10.1109/TEVC.2008.2004261

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) http://dx.doi.org/10.1145/1254960.1254986

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

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)

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)

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)

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) http://dx.doi.org/10.1145/1399504.1360625

Kovar, L., Gleicher, M., Pighin, F.: Motion graphs. In: Proceedings of SIGGRAPH 2002, vol. 21, pp. 473–482. ACM Press, New York (2002) http://dx.doi.org/10.1145/566570.566605

Ko, H., Badler, N.I.: Animating human locomotion with inverse dynamics. IEEE Computer Graphics and Applications 16(2), 50–59 (1996) http://dx.doi.org/10.1109/38.486680


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