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Applying Evolutionary Computation Operators for Automatic Human Motion Generation in Computer Animation and Video Games

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Intelligent Distributed Computing XII (IDC 2018)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 798))

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Abstract

This paper presents an evolutionary computation scheme for automatic human motion generation in computer animation and video games. Given a set of identical physics-driven skeletons seated on the ground as an initial pose (similar for all skeletons), the method applies forces on selected bones seeking for a final stable pose with all skeletons standing. Such forces are initially random but then modulated by a set of evolutionary operators (selection, reproduction, and mutation) to make the digital characters learn to stand up by themselves. An illustrative example is discussed in detail to show the performance of this approach. This method can readily be extended to other skeleton configurations and other interesting motions with little modification. Our approach represents a significant first step towards automatic generation of motion routines by applying evolutionary operators.

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References

  1. Díaz, G., Iglesias, A.: Swarm intelligence scheme for pathfinding and action planning of non-player characters on a last-generation video game. In: Advances in Intelligent Systems and Computing, vol. 514, pp. 343–353 (2017)

    Google Scholar 

  2. Díaz, G., Iglesias, A.: Intelligent behavioral design of non-player characters in a FPS video game through PSO. In: Advances in Swarm Intelligence. Lecture Notes in Computer Science, vol. 10385, pp. 246–254 (2017)

    Google Scholar 

  3. Iglesias, A., Luengo, F.: Intelligent agents for virtual worlds. In: Proceedings of CW 2004, Tokyo, Japan, pp. 62–69. IEEE Computer Society Press, Los Alamitos (2004)

    Google Scholar 

  4. Iglesias, A., Luengo, F.: New goal selection scheme for behavioral animation of intelligent virtual agents. IEICE Trans. Inf. Syst. E88–D(5), 865–871 (2005)

    Article  Google Scholar 

  5. Iglesias, A., Luengo, F.: AI framework for decision modeling in behavioral animation of virtual avatars. LNCS, vol. 4488, pp. 89–96 (2007)

    Chapter  Google Scholar 

  6. Mori, H., Toyama, F., Shoji, K.: Optimization of character gaze behavior animation using an interactive genetic algorithm. Int. J. Asia Digit. Art Des. 21(1–4), 25–31 (2017)

    Google Scholar 

  7. Schwab, B.: AI Game Engine Programming, 2nd edn. Course Technology, Boston (2009)

    Google Scholar 

  8. Sims, K.: Artificial evolution for computer graphics. In: ACM SIGGRAPH, pp. 319–328 (1991)

    Article  Google Scholar 

  9. Sims, K.: Evolving virtual creatures. In: ACM SIGGRAPH, pp. 15–22 (1994)

    Google Scholar 

  10. Woodcock, S.: Game AI: the state of the industry 2000–2001: it’s not just art, it’s engineering. In: Game Developer, August 2001, pp. 36–44 (2001)

    Google Scholar 

  11. Xu, K., Zhang, H., Daniel Cohen-Or, D., Chen, B.: Fit and diverse: set evolution for inspiring 3D shape galleries. ACM Trans. Graph. 31(4), Article No. 57 (2012)

    Article  MathSciNet  Google Scholar 

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Acknowledgements

This research work has received funding from the project PDE-GIR of the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 778035, the Spanish Ministry of Economy and Competitiveness (Computer Science National Program) under grant #TIN2017-89275-R of the Agencia Estatal de InvestigaciĂ³n and European Funds FEDER (AEI/FEDER, UE), and the project #JU12, jointly supported by public body SODERCAN and European Funds FEDER (SODERCAN/FEDER UE).

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Correspondence to Andrés Iglesias .

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de la Vega-Hazas, L., Calatayud, F., Iglesias, A. (2018). Applying Evolutionary Computation Operators for Automatic Human Motion Generation in Computer Animation and Video Games. In: Del Ser, J., Osaba, E., Bilbao, M., Sanchez-Medina, J., Vecchio, M., Yang, XS. (eds) Intelligent Distributed Computing XII. IDC 2018. Studies in Computational Intelligence, vol 798. Springer, Cham. https://doi.org/10.1007/978-3-319-99626-4_22

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  • DOI: https://doi.org/10.1007/978-3-319-99626-4_22

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  • Online ISBN: 978-3-319-99626-4

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