Abstract
In this chapter, we introduce concepts in computer animation, starting with physics-based animation. We revise the main steps of the pipeline involved: (1) geometric modeling of the scene; (2) the physical model describing the dynamics and interaction of objects therein; (3) computer simulation of the model; (4) rendering. Then, machine learning concepts regarding training and learning taxonomy (supervised, unsupervised, semi-supervised, and reinforcement learning) are discussed, aiming to prepare the way to introduce the main goal of this work: fluid animation based on deep learning techniques, which is motivated by the universality of the computational model of neural networks besides the possibility of generating surrogate models with the capability of producing predictions faster than traditional approaches, from the knowledge gained in the training process. Finally, the organization of the following sections is outlined.
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Antonio Giraldi, G., Almeida, L.R.d., Lopes Apolinário Jr., A., Silva, L.T.d. (2023). Introductory Material to Animation and Learning. In: Deep Learning for Fluid Simulation and Animation. SpringerBriefs in Mathematics. Springer, Cham. https://doi.org/10.1007/978-3-031-42333-8_1
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