Physics-Based Animation

Meekyoung Kim, Gerard Pons-Moll, Sergi Pujades, Sungbae Bang, Jinwwok Kim, Michael Black, Sung-Hee Lee

Data driven models of human poses and soft-tissue deformations can produce very realistic results, but they only model the visible surface of the human body and cannot create skin deformation due to interactions with the environment. Physical simulations can generalize to external forces, but their parameters are difficult to control. In this paper, we present a layered volumetric human body model learned from data. Our model is composed of a data-driven inner layer and a physics-based external layer. The inner layer is driven with a volumetric statistical body model (VSMPL). The soft tissue layer consists of a tetrahedral mesh that is driven using the finite element method (FEM). Model parameters, namely the segmentation of the body into layers and the soft tissue elasticity, are learned directly from 4D registrations of humans exhibiting soft tissue deformations. The learned two layer model is a realistic full-body avatar that generalizes to novel motions and external forces. Experiments show that the resulting avatars produce realistic results on held out sequences and react to external forces. Moreover, the model supports the retargeting of physical properties from one avatar when they share the same topology.

Data-Driven Physics for Human Soft Tissue Animation

Fernando de Goes, Doug L. James

We introduce a new technique for real-time physically based volume sculpting of virtual elastic materials. Our formulation is based on the elastic response to localized force distributions associated with common modeling primitives such as grab, scale, twist, and pinch. The resulting brush-like displacements correspond to the regularization of fundamental solutions of linear elasticity in infinite 2D and 3D media. These deformations thus provide the realism and plausibility of volumetric elasticity, and the interactivity of closed-form analytical solutions. To finely control our elastic deformations, we also construct compound brushes with arbitrarily fast spatial decay. Furthermore, pointwise constraints can be imposed on the displacement field and its derivatives via a single linear solve. We demonstrate the versatility and efficiency of our method with multiple examples of volume sculpting and image editing.

Regularized Kelvinlets: Sculpting Brushes based on Fundamental Solutions of Elasticity

Bohan Wang, Yili Zhao, Jernej Barbic

Botanical simulation plays an important role in many fields including visual effects, games and virtual reality. Previous plant simulation research has focused on computing physically based motion, under the assumption that the material properties are known. It is too tedious and impractical to manually set the spatially-varying material properties of complex trees. In this paper, we give a method to set the mass density, stiffness and damping properties of individual tree components (branches and leaves) using a small number of intuitive parameters. Our method is rooted in plant biomechanics literature and builds upon power laws observed in real botanical systems. We demonstrate our materials by simulating them using offline and model-reduced FEM simulators. Our parameters can be tuned directly by artists; but we also give a technique to infer the parameters from ground truth videos of real trees. Our materials produce tree animations that look much more similar to real trees than previous methods, as evidenced by our user study and experiments.

Botanical Materials Based on Biomechanics

Alexandru-Eugen Ichim, Petr Kadlecek, Ladislav Kavan, Mark Pauly

We present a novel physics-based approach to facial animation. Contrary to commonly used generative methods, our solution computes facial expressions by minimizing a set of non-linear potential energies that model the physical interaction of passive flesh, active muscles, and rigid bone structures. By integrating collision and contact handling into the simulation, our algorithm avoids inconsistent poses commonly observed in generative methods such as blendshape rigs. A novel muscle activation model leads to a robust optimization that faithfully reproduces complex facial articulations. We show how person-specific simulation models can be built from a few expression scans with a minimal data acquisition process and an almost entirely automated processing pipeline. Our method supports temporal dynamics due to inertia or external forces, incorporates skin sliding to avoid unnatural stretching, and offers full control of the simulation parameters, which enables a variety of advanced animation effects. For example, slimming or fattening the face is achieved by simply scaling the volume of the soft tissue elements. We show a series of application demos, including artistic editing of the animation model, simulation of corrective facial surgery, or dynamic interaction with external forces and objects.

Phace: Physics-based Face Modeling and Animation