Physics-Based Animation

Woojong Koh, Rahul Narain, James F. O’Brien

This paper describes a method for view-dependent cloth simulation using dynamically adaptive mesh refinement and coarsening. Given a prescribed camera motion, the method adjusts the criteria controlling refinement to account for visibility and apparent size in the camera’s view. Objectionable dynamic artifacts are avoided by anticipative refinement and smoothed coarsening. This approach preserves the appearance of detailed cloth throughout the animation while avoiding the wasted effort of simulating details that would not be discernible to the viewer. The computational savings realized by this method increase as scene complexity grows, producing a 2x speed-up for a single character and more than 4x for a small group.

View-Dependent Adaptive Cloth Simulation

James Gregson, Ivo Irkhe, Nils Thuerey, Wolfgang Heidrich

We explore the connection between fluid capture, simulation and proximal methods, a class of algorithms commonly used for inverse problems in image processing and computer vision. Our key finding is that the proximal operator constraining fluid velocities to be divergence-free is directly equivalent to the pressure-projection methods commonly used in incompressible flow solvers. This observation lets us treat the inverse problem of fluid tracking as a constrained flow problem all while working in an efficient, modular framework. In addition it lets us tightly couple fluid simulation into flow tracking, providing a global prior that significantly increases tracking accuracy and temporal coherence as compared to previous techniques. We demonstrate how we can use these improved results for a variety of applications, such as re-simulation, detail enhancement, and domain modification. We furthermore give an outlook of the applications beyond fluid tracking that our proximal operator framework could enable by exploring the connection of deblurring and fluid guiding.

From Capture to Simulation – Connecting Forward and Inverse Problems in Fluids

Bo Reng, Chenfeng Li, Xiao Yan, Ming C. Lin, Javier Bonet, Shi-Min Hu

This paper presents a versatile and robust SPH simulation approach for multiple-fluid flows. The spatial distribution of different phases or components is modeled using the volume fraction representation, the dynamics of multiple-fluid flows is captured by using an improved mixture model, and a stable and accurate SPH formulation is rigorously derived to resolve the complex transport and transformation processes encountered in multiple-fluid flows. The new approach can capture a wide range of realworld multiple-fluid phenomena, including mixing/unmixing of miscible and immiscible fluids, diffusion effect and chemical reaction etc. Moreover, the new multiple-fluid SPH scheme can be readily integrated into existing state-of-the-art SPH simulators, and the multiple-fluid simulation is easy to set up. Various examples are presented to demonstrate the effectiveness of our approach.

Multiple-Fluid SPH Simulation Using a Mixture Model

Sofien Bouaziz, Sebastian Martin, Tiantian Liu, Ladislav Kavan, Mark Pauly

We present a new method for implicit time integration of physical systems. Our approach builds a bridge between nodal Finite Element methods and Position Based Dynamics, leading to a simple, efficient, robust, yet accurate solver that supports many different types of constraints. We propose specially designed energy potentials that can be solved efficiently using an alternating optimization approach. Inspired by continuum mechanics, we derive a set of continuum-based
potentials that can be efficiently incorporated within our solver. We demonstrate the generality and robustness of our approach in many different applications ranging from the simulation of solids, cloths, and shells, to example-based  simulation. Comparisons to Newton-based and Position Based Dynamics solvers highlight the benefits of our formulation.

Projective Dynamics: Fusing Constraint Projections for Fast Simulation

Matthias Mueller, Nuttapong Chentanez, Tae-Yong Kim, Miles Macklin

We propose a new set of constraints within the Position Based Dynamics (PBD) framework that allow the control of strain in directions that are independent of the edge directions of the simulation mesh. Instead of constraining distances between points, we constrain the entries of the Green – St Venant strain tensor. Varying the stiffness values corresponding to the individual strain coefficients lets us simulate anisotropic behavior. By working with Green’s rotation-independent, non-linear strain tensor directly we do not have to perform a polar decomposition of the deformation gradient as in most strain limiting approaches. In addition, we propose a modification of the constraints corresponding to the diagonal entries of the strain tensor such that they can be solved in a single step and a modification of the constraints corresponding to the off-diagonal entries to decouple stretch from shear resistance. By formulating the constraints within the PBD framework, they can be used not only for strain limiting but to perform the actual simulation of the deformable object whereas traditional strain limiting methods have to be paired with a separate simulation method.

Strain-Based Dynamics

Menglei Chai, Changxi Zheng, Kun Zhou

Realistic hair animation is a crucial component in depicting virtual characters in interactive applications. While much progress has been made in high-quality hair simulation, the overwhelming computation cost hinders similar fidelity in realtime simulations. To bridge this gap, we propose a data-driven solution. Building upon precomputed simulation data, our approach constructs a reduced model to optimally represent hair motion characteristics with a small number of guide hairs and the corresponding interpolation relationships. At runtime, utilizing such a reduced model, we only simulate guide hairs that capture the general hair motion and interpolate all rest strands. We further propose a hair correction method that corrects the resulting hair motion with a position-based model to resolve hair collisions and thus captures motion details. Our hair simulation method enables a simulation of a full head of hairs with over 150K strands in realtime. We demonstrate the efficacy and robustness of our method with various hairstyles and driven motions (e.g., head movement and wind force), and compared against full simulation results that does not appear in the training data.

A Reduced Model for Interactive Hairs

Miles Macklin, Matthias Müller, Nuttapong Chentanez, and Tae-Yong Kim

We present a unified dynamics framework for real-time visual effects. Using particles connected by constraints as our fundamental building block allows us to treat contact and collisions in a unified manner, and we show how this representation is flexible enough to model gases, liquids, deformable solids, rigid bodies and clothing with two-way interactions. We address some common problems with traditional particle based methods and describe a parallel constraint solver based on position based dynamics that is efficient enough for real-time applications.

Unified Particle Physics for Real-Time Applications

Liwen Hu, Chongyang Ma, Linjie Luo, and Hao Li

We introduce a data-driven hair capture framework based on example strands generated through hair simulation. Our method can robustly reconstruct faithful 3D hair models from unprocessed input point clouds with large amounts of outliers. Current state-of-the-art techniques use geometrically-inspired heuristics to derive global hair strand structures, which can yield implausible hair strands for hairstyles involving large occlusions, multiple layers, or wisps of varying lengths. We address this problem using a voting-based fitting algorithm to discover structurally plausible configurations among the locally grown hair segments from a database of simulated examples. To generate these examples, we exhaustively sample the simulation configurations within the feasible parameter space constrained by the current input hairstyle. The number of necessary simulations can be further reduced by leveraging symmetry and constrained initial conditions. The final hairstyle can then be structurally represented by a limited number of examples. To handle constrained hairstyles such as a ponytail of which realistic simulations are more difficult, we allow the user to sketch a few strokes to generate strand examples through an intuitive interface. Our approach focuses on robustness and generality. Since our method is structurally plausible by construction, we ensure an improved control during hair digitization and avoid implausible hair synthesis for a wide range of hairstyles.

Robust Hair Capture Using Simulated Examples

Timothy R. Langlois and Doug L. James

In this paper, we introduce Inverse-Foley Animation, a technique for optimizing rigid-body animations so that contact events are synchronized with input sound events. A precomputed database of randomly sampled rigid-body contact events is used to build a contact-event graph, which can be searched to determine a plausible sequence of contact events synchronized with the input sound’s events. To more easily find motions with matching contact times, we allow transitions between simulated contact events using a motion blending formulation based on modified contact impulses. We fine tune synchronization by slightly retiming ballistic motions. Given a sound, our system can synthesize synchronized motions using graphs built with hundreds of thousands of precomputed motions, and millions of contact events. Our system is easy to use, and has been used to plan motions for hundreds of sounds, and dozens of rigid-body models.

Inverse-Foley Animation: Synchronizing Rigid-Body Motions to Sound

Siwang Li, Jin Huang, Fernando de Goes, Xiaogang Jin, Hujun Bao, and Mathieu Desbrun

We present a novel method for elastic animation editing with spacetime constraints. In a sharp departure from previous approaches, we not only optimize control forces added to a linearized dynamic model, but also optimize material properties to better match user constraints and provide plausible and consistent motion. Our approach achieves efficiency and scalability by performing all computations in a reduced rotation-strain (RS) space constructed with both cubature and geometric reduction, leading to two orders of magnitude improvement over the original RS method. We demonstrate the utility and versatility of our method in various applications, including motion editing, pose interpolation, and estimation of material parameters from existing animation sequences.

Space-Time Editing of Elastic Motions through Material Optimization and Reduction