Kenny Erleben

Interactive Simulation of Rigid Body Dynamics in Computer Graphics

Interactive rigid body simulation is an important part of many modern computer tools, which no authoring tool nor game engine can do without. Such high‐performance computer tools open up new possibilities for changing how designers, engineers, modelers and animators work with their design problems. This paper is a self contained state‐of‐the‐art report on the physics, the models, the numerical methods and the algorithms used in interactive rigid body simulation all of which have evolved and matured over the past 20 years. Furthermore, the paper communicates the mathematical and theoretical details in a pedagogical manner. This paper is not only a stake in the sand on what has been done, it also seeks to give the reader deeper insights to help guide their future research.

Velocity-based shock propagation for multibody dynamics animation

Multibody dynamics are used in interactive and real-time applications, ranging from computer games to virtual prototyping, and engineering. All these areas strive towards faster and larger scale simulations. Particularly challenging are large-scale simulations with highly organized and structured stacking. We present a stable, robust, and versatile method for multibody dynamics simulation. Novel contributions include a new, explicit, fixed time-stepping scheme for velocity-based complementarity formulations using shock propagation with a simple reliable implementation strategy for an iterative complementarity problem solver specifically optimized for multibody dynamics.

Photon differentials

A number of popular global illumination algorithms uses density estimation to approximate indirect illumination. The density estimate is performed on finite points -- particles -- generated by a stochastic sampling of the scene. In the course of the sampling, particles, representing light, are stochastically emitted from the light sources and reflected around the scene. The sampling induces noise, which in turn is handled by the density estimate during the illumination reconstruction. Unfortunately, this noise reduction imposes a systematic error (bias), which is seen as a blurring of prominent illumination features. This is often not desirable as these may lose clarity or vanish altogether. We present an accurate method for reconstruction of indirect illumination with photon mapping. Instead of reconstructing illumination using classic density estimation on finite points, we use the correlation of light footprints, created by using Ray Differentials during the light pass. This procedure gives a high illumination accuracy, improving the trade-off between bias and variance considerable as compared to traditional particle tracing algorithms. In this way we preserve structures in indirect illumination.

Optimization-based Fluid Simulation on Unstructured Meshes

We present a novel approach to fluid simulation, allowing us to take into account the surface energy in a precise manner. This new approach combines a novel, topology-adaptive approach to deformable interface tracking, called the deformable simplicial complexes method (DSC) with an optimization-based, linear finite element method for solving the incompressible Euler equations. The deformable simplicial complexes track the surface of the fluid: the fluid-air interface is represented explicitly as a piecewise linear surface which is a subset of tetrahedralization of the space, such that the interface can be also represented implicitly as a set of faces separating tetrahedra marked as inside from the ones marked as outside. This representation introduces insignificant and controllable numerical diffusion, allows robust topological adaptivity and provides both a volumetric finite element mesh for solving the fluid dynamics equations as well as direct access to the interface geometry data, making inclusion of a new surface energy term feasible. Furthermore, using an unstructured mesh makes it straightforward to handle curved solid boundaries and gives us a possibility to explore several fluid-solid interaction scenarios.

Multiphase flow of immiscible fluids on unstructured moving meshes

In this paper, we present a method for animating multiphase flow of immiscible fluids using unstructured moving meshes. Our underlying discretization is an unstructured tetrahedral mesh, the deformable simplicial complex (DSC), that moves with the flow in a Lagrangian manner. Mesh optimization operations improve element quality and avoid element inversion. In the context of multiphase flow, we guarantee that every element is occupied by a single fluid and, consequently, the interface between fluids is represented by a set of faces in the simplicial complex. This approach ensures that the underlying discretization matches the physics and avoids the additional book-keeping required in grid-based methods where multiple fluids may occupy the same cell. Our Lagrangian approach naturally leads us to adopt a finite element approach to simulation, in contrast to the finite volume approaches adopted by a majority of fluid simulation techniques that use tetrahedral meshes. We characterize fluid simulation as an optimization problem allowing for full coupling of the pressure and velocity fields and the incorporation of a second-order surface energy. We introduce a preconditioner based on the diagonal Schur complement and solve our optimization on the GPU. We provide the results of parameter studies as well as a performance analysis of our method, together with suggestions for performance optimization.

Tetrahedral Mesh Improvement Using Multi-face Retriangulation

In this paper we propose a simple technique for tetrahedral mesh improvement without inserting Steiner vertices, concentrating mainly on boundary conforming meshes. The algorithm makes local changes to the mesh to remove tetrahedra which are poor according to some quality criterion. While the algorithm is completely general with regard to quality criterion, we target improvement of the dihedral angle. The central idea in our algorithm is the introduction of a new local operation called multi-face retriangulation (MFRT) which supplements other known local operations. Like in many previous papers on tetrahedral mesh improvement, our algorithm makes local changes to the mesh to reduce an energy measure which reflects the quality criterion. The addition of our new local operation allows us to advance the mesh to a lower energy state in cases where no other local change would lead to a reduction. We also make use of the edge collapse operation in order to reduce the size of the mesh while improving its quality. With these operations, we demonstrate that it is possible to obtain a significantly greater improvement to the worst dihedral angles than using the operations from the previous works, while keeping the mesh complexity as low as possible.

A Triangle Bending Constraint Model for Position-Based Dynamics

We present a novel bending model and constraint creation method for position-based dynamics. Our new bending model is introduced as an alternative to the current state-of-the-art dihedral bending model. Our model is motivated by geometric principles and operates on virtual triangles. It has the same cheap computational cost as the stick constraint model but with higher simulation quality and faster convergence than the dihedral bending model. Along with the model a new global bending parameter is introduced to control the curvature deformation at high precision compared to the traditional stiffness constant. Further, we propose a new constraint creation method that we believe is well suited for the triangle bending model and less affected by the underlying mesh tessellation.

Mathematical foundation of the optimization-based fluid animation method

We present the mathematical foundation of a fluid animation method for unstructured meshes. Key contributions not previously treated are the extension to include diffusion forces and higher order terms of non-linear force approximations. In our discretization we apply a fractional step method to be able to handle advection in a numerically simple Lagrangian approach. Following this a finite element method is used for the remaining terms of the fractional step method. The key to deriving a discretization for the diffusion forces lies in restating the momentum equations in terms of a Newtonian stress tensor. Rather than applying a straightforward temporal finite difference method followed by a projection method to enforce incompressibility as done in the stable fluids method, the last step of the fractional step method is rewritten as an optimization problem to make it easy to incorporate non-linear force terms such as surface tension.

Multiphase Flow of Immiscible Fluids on Unstructured Moving Meshes

In this paper, we present a method for animating multiphase flow of immiscible fluids using unstructured moving meshes. Our underlying discretization is an unstructured tetrahedral mesh, the deformable simplicial complex (DSC), that moves with the flow in a Lagrangian manner. Mesh optimization operations improve element quality and avoid element inversion. In the context of multiphase flow, we guarantee that every element is occupied by a single fluid and, consequently, the interface between fluids is represented by a set of faces in the simplicial complex. This approach ensures that the underlying discretization matches the physics and avoids the additional book-keeping required in grid-based methods where multiple fluids may occupy the same cell. Our Lagrangian approach naturally leads us to adopt a finite element approach to simulation, in contrast to the finite volume approaches adopted by a majority of fluid simulation techniques that use tetrahedral meshes. We characterize fluid simulation as an optimization problem allowing for full coupling of the pressure and velocity fields and the incorporation of a second-order surface energy. We introduce a preconditioner based on the diagonal Schur complement and solve our optimization on the GPU. We provide the results of parameter studies as well as a performance analysis of our method, together with suggestions for performance optimization.

GPU accelerated likelihoods for stereo-based articulated tracking

For many years articulated tracking has been an active research topic in the computer vision community. While working solutions have been suggested, computational time is still problematic. We present a GPU implementation of a ray-casting based likelihood model that is orders of magnitude faster than a traditional CPU implementation. We explain the non-intuitive steps required to attain an optimized GPU implementation, where the dominant part is to hide the memory latency effectively. Benchmarks show that computations which previously required several minutes, are now performed in few seconds.