Manteaux, Pierre; Wojtan, ChrisIST Austria ; Narain, Rahul; Redon, Stéphane; Faure, François; Cani, Marie
One of the major challenges in physically based modelling is making simulations efficient. Adaptive models provide an essential solution to these efficiency goals. These models are able to self-adapt in space and time, attempting to provide the best possible compromise between accuracy and speed. This survey reviews the adaptive solutions proposed so far in computer graphics. Models are classified according to the strategy they use for adaptation, from time-stepping and freezing techniques to geometric adaptivity in the form of structured grids, meshes and particles. Applications range from fluids, through deformable bodies, to articulated solids.
Computer Graphics Forum
This work was partly supported by the starting grants ADAPT and BigSplash, as well as the advanced grant EXPRESSIVE from the European Research Council (ERC-2012-StG_20111012, ERC-2014-StG_638176 and ERC-2011-ADG_20110209).
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Manteaux P, Wojtan CJ, Narain R, Redon S, Faure F, Cani M. Adaptive physically based models in computer graphics. Computer Graphics Forum. 2017;36(6):312-337. doi:10.1111/cgf.12941
Manteaux, P., Wojtan, C. J., Narain, R., Redon, S., Faure, F., & Cani, M. (2017). Adaptive physically based models in computer graphics. Computer Graphics Forum. Wiley-Blackwell. https://doi.org/10.1111/cgf.12941
Manteaux, Pierre, Christopher J Wojtan, Rahul Narain, Stéphane Redon, François Faure, and Marie Cani. “Adaptive Physically Based Models in Computer Graphics.” Computer Graphics Forum. Wiley-Blackwell, 2017. https://doi.org/10.1111/cgf.12941.
P. Manteaux, C. J. Wojtan, R. Narain, S. Redon, F. Faure, and M. Cani, “Adaptive physically based models in computer graphics,” Computer Graphics Forum, vol. 36, no. 6. Wiley-Blackwell, pp. 312–337, 2017.
Manteaux P, Wojtan CJ, Narain R, Redon S, Faure F, Cani M. 2017. Adaptive physically based models in computer graphics. Computer Graphics Forum. 36(6), 312–337.
Manteaux, Pierre, et al. “Adaptive Physically Based Models in Computer Graphics.” Computer Graphics Forum, vol. 36, no. 6, Wiley-Blackwell, 2017, pp. 312–37, doi:10.1111/cgf.12941.
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