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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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 Investigación 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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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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