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, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
4 NANO-D - Algorithms for Modeling and Simulation of Nanosystems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
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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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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