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Adaptive Physically Based Models in Computer Graphics

Pierre-Luc Manteaux 1 Chris Wojtan 2 Rahul Narain 3 Stéphane Redon 4 François Faure 1 Marie-Paule Cani 1
1 IMAGINE - Intuitive Modeling and Animation for Interactive Graphics & Narrative Environments
Inria Grenoble - Rhône-Alpes, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann
4 NANO-D [2014-2018] - Algorithms for Modeling and Simulation of Nanosystems [2014-2018]
Inria Grenoble - Rhône-Alpes, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann
Abstract : One of the major challenges in physically-based modeling 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.
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https://hal.inria.fr/hal-01367170
Contributor : Pierre-Luc Manteaux <>
Submitted on : Thursday, September 15, 2016 - 5:02:43 PM
Last modification on : Thursday, November 19, 2020 - 1:02:13 PM
Long-term archiving on: : Friday, December 16, 2016 - 3:47:02 PM

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Pierre-Luc Manteaux, Chris Wojtan, Rahul Narain, Stéphane Redon, François Faure, et al.. Adaptive Physically Based Models in Computer Graphics. Computer Graphics Forum, Wiley, 2017, 36 (6), pp.312-337 ⟨10.1111/cgf.12941⟩. ⟨hal-01367170⟩

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