Realistic Hair Simulation: Animation and Rendering

International audienceThe last five years have seen a profusion of innovative solutions to one of the most challenging tasks in character synthesis: hair simulation. This class covers both recent and novel research ideas in hair animation and rendering, and presents time tested industrial practices that resulted in spectacular imagery

Real-time simulation and visualisation of cloth using edge-based adaptive meshes

Real-time rendering and the animation of realistic virtual environments and characters has progressed at a great pace, following advances in computer graphics hardware in the last decade. The role of cloth simulation is becoming ever more important in the quest to improve the realism of virtual environments. The real-time simulation of cloth and clothing is important for many applications such as virtual reality, crowd simulation, games and software for online clothes shopping. A large number of polygons are necessary to depict the highly exible nature of cloth with wrinkling and frequent changes in its curvature. In combination with the physical calculations which model the deformations, the effort required to simulate cloth in detail is very computationally expensive resulting in much diffculty for its realistic simulation at interactive frame rates. Real-time cloth simulations can lack quality and realism compared to their offline counterparts, since coarse meshes must often be employed for performance reasons. The focus of this thesis is to develop techniques to allow the real-time simulation of realistic cloth and clothing. Adaptive meshes have previously been developed to act as a bridge between low and high polygon meshes, aiming to adaptively exploit variations in the shape of the cloth. The mesh complexity is dynamically increased or refined to balance quality against computational cost during a simulation. A limitation of many approaches is they do not often consider the decimation or coarsening of previously refined areas, or otherwise are not fast enough for real-time applications. A novel edge-based adaptive mesh is developed for the fast incremental refinement and coarsening of a triangular mesh. A mass-spring network is integrated into the mesh permitting the real-time adaptive simulation of cloth, and techniques are developed for the simulation of clothing on an animated character

Fast soft-tissue deformations with FEM

Soft body simulation has been a very active research area in computer animation since Baraff and Witkin's 1998 work on cloth simulation, which led Pixar to start using such techniques in all of its animated movies that followed. Many challenges in these simulations come from different roots. From a numerical point of view, deformable systems are large sparse problems that can become numerically unstable at surprising rates and may need to be modified at each time-step. From a mathematical point of view, hyperelastic models defined by continuum mechanics need to be derived, established and configured. And from the geometric side, physical interaction with the environment and self-collisions may need to be detected and introduced into the solver. It is a fact that the Computer Graphics academia primarily focuses on offline methods, both for rendering and simulation. At the same time, the advances from the industry mainly apply to real-time rendering. However, we wondered how such high-quality simulation methods would map to a real-time use case. In this thesis, we delve into the simulation system used by Pixar's Fizt2 simulator, based on the Finite Element Method, and investigate how to apply the same techniques in real-time while preserving robustness and fidelity, altogether providing the user with some interaction mechanisms. A 3D engine for simulating deformable materials has been developed following the described models, with an interactive interface that allows the definition and configuration of scenes and later interaction with the simulation

Multi-Scale Models to Simulate Interactions between Liquid and Thin Structures

In this dissertation, we introduce a framework for simulating the dynamics between liquid and thin structures, including the effects of buoyancy, drag, capillary cohesion, dripping, and diffusion. After introducing related works, Part I begins with a discussion on the interactions between Newtonian fluid and fabrics. In this discussion, we treat both the fluid and the fabrics as continuum media; thus, the physical model is built from mixture theory. In Part II, we discuss the interactions between Newtonian fluid and hairs. To have more detailed dynamics, we no longer treat the hairs as continuum media. Instead, we treat them as discrete Kirchhoff rods. To deal with the thin layer of liquid that clings to the hairs, we augment each hair strand with a height field representation, through which we introduce a new reduced-dimensional flow model to solve the motion of liquid along the longitudinal direction of each hair. In addition, we develop a faithful model for the hairs' cohesion induced by surface tension, where a penalty force is applied to simulate the collision and cohesion between hairs. To enable the discrete strands interact with continuum-based, shear-dependent liquid, in Part III, we develop models that account for the volume change of the liquid as it passes through strands and the momentum exchange between the strands and the liquid. Accordingly, we extend the reduced-dimensional flow model to simulate liquid with elastoviscoplastic behavior. Furthermore, we use a constraint-based model to replace the penalty-force model to handle contact, which enables an accurate simulation of the frictional and adhesive effects between wet strands. We also present a principled method to preserve the total momentum of a strand and its surface flow, as well as an analytic plastic flow approach for Herschel-Bulkley fluid that enables stable semi-implicit integration at larger time steps. We demonstrate a wide range of effects, including the challenging animation scenarios involving splashing, wringing, and colliding of wet clothes, as well as flipping of hair, animals shaking, spinning roller brushes from car washes being dunked in water, and intricate hair coalescence effects. For complex liquids, we explore a series of challenging scenarios, including strands interacting with oil paint, mud, cream, melted chocolate, and pasta sauce

Robust, Efficient, and Accurate Contact Algorithms

Robust, efficient, and accurate contact response remains a challenging problem in the simulation of deformable materials. Contact models should robustly handle contact between geometry by preventing interpenetrations. This should be accomplished while respecting natural laws in order to maintain physical correctness. We simultaneously desire to achieve these criteria as efficiently as possible to minimize simulation runtimes. Many methods exist that partially achieve these properties, but none yet fully attain all three. This thesis investigates existing methodologies with respect to these attributes, and proposes a novel algorithm for the simulation of deformable materials that demonstrate them all. This new method is analyzed and optimized, paving the way for future work in this simplified but powerful manner of simulation

Structure Preserving and Scalable Simulation of Colliding Systems

Predictive computational tools to study granular materials are important in fields ranging from the geosciences and civil engineering to computer graphics. The simulation of granular materials, however, presents many challenges. The behavior of a granular medium is fundamentally multi-scale, with pair-wise interactions between discrete granules able to influence the continuum-scale evolution of a bulk material. Computational techniques for studying granular materials must therefore contend with this multi-scale nature. This research first addresses both the question of how to accurately model interactions between grains and the question of how to achieve multi-scale simulations of granular materials. We propose a novel rigid body contact model and a time integration technique that, for the first time, are able to simultaneously capture five key features of rigid body impact. We further validate this new model and time integration method by reproducing computationally challenging phenomena from granular physics. We next propose a technique to couple discrete and continuum models of granular materials to one another. This hybrid model reveals a family of possible discretizations suitable for simulation. We derive an explicit integration technique from this framework that is able to capture phenomena previously reserved for discrete treatments, including frictional jamming, while treating bulk regions of the material with a continuum model. To effectively handle the large plastic deformations inherent in the evolution of a granular medium, we further propose a method to dynamically update which regions are treated with a discrete model and which regions are treated with a continuum model. We demonstrate that hybrid simulations of a dynamically evolving granular material are possible and practical, and lay the foundation for further algorithmic development in this space. Finally, as the the tools used in computational science and engineering become progressively more complex, the ability to effectively train students in the field becomes increasingly important. We address the question of how to train students from a computer science background in numerical computation techniques by proposing a new system to automatically vet and identify problems in numerical simulations. This system has been deployed at the undergraduate and graduate level in a course on physical simulation at Columbia University, and has increased both student retention and student satisfaction with the course

Visual modeling and simulation of multiscale phenomena

Many large-scale systems seen in real life, such as human crowds, fluids, and granular materials, exhibit complicated motion at many different scales, from a characteristic global behavior to important small-scale detail. Such multiscale systems are computationally expensive for traditional simulation techniques to capture over the full range of scales. In this dissertation, I present novel techniques for scalable and efficient simulation of these large, complex phenomena for visual computing applications. These techniques are based on a new approach of representing a complex system by coupling together separate models for its large-scale and fine-scale dynamics. In fluid simulation, it remains a challenge to efficiently simulate fine local detail such as foam, ripples, and turbulence without compromising the accuracy of the large-scale flow. I present two techniques for this problem that combine physically-based numerical simulation for the global flow with efficient local models for detail. For surface features, I propose the use of texture synthesis, guided by the physical characteristics of the macroscopic flow. For turbulence in the fluid motion itself, I present a technique that tracks the transfer of energy from the mean flow to the turbulent fluctuations and synthesizes these fluctuations procedurally, allowing extremely efficient visual simulation of turbulent fluids. Another large class of problems which are not easily handled by traditional approaches is the simulation of very large aggregates of discrete entities, such as dense pedestrian crowds and granular materials. I present a technique for crowd simulation that couples a discrete per-agent model of individual navigation with a novel continuum formulation for the collective motion of pedestrians. This approach allows simulation of dense crowds of a hundred thousand agents at near-real-time rates on desktop computers. I also present a technique for simulating granular materials, which generalizes this model and introduces a novel computational scheme for friction. This method efficiently reproduces a wide range of granular behavior and allows two-way interaction with simulated solid bodies. In all of these cases, the proposed techniques are typically an order of magnitude faster than comparable existing methods. Through these applications to a diverse set of challenging simulation problems, I demonstrate the benefits of the proposed approach, showing that it is a powerful and versatile technique for the simulation of a broad range of large and complex systems

Interactive simulation and rendering of fluids on graphics hardware

Computational uid dynamics can be used to reproduce the complex motion of fluids for use in computer graphics, but the simulation and rendering are both highly computationally intensive. In the past performing these tasks on the CPU could take many minutes per frame, especially for large scale scenes at high levels of detail, which limited their usage to offline applications such as in film and media. However, using the massive parallelism of GPUs, it is nowadays possible to produce uid visual effects in real time for interactive applications such as games. We present such an interactive simulation using the CUDA GPU computing environment and OpenGL graphics API. Smoothed Particle Hydrodynamics (SPH) is a popular particle-based fluid simulation technique that has been shown to be well suited to acceleration on the GPU. Our work extends an existing GPU-based SPH implementation by incorporating rigid body interaction and rendering. Solid objects are represented using particles to accumulate hydrodynamic forces from surrounding fluid, while motion and collision handling are handled by the Bullet Physics library on the CPU. Our system demonstrates two-way coupling with multiple objects floating, displacing fluid and colliding with each other. For rendering we compare the performance and memory consumption of two approaches, splatting and raycasting, we also describe the visual characteristics of each. In our evaluation we consider a target of between 24 and 30 fps to be sufficient for smooth interaction and aim to determine the performance impact of our new features. We begin by establishing a performance baseline and find that the original system runs smoothly up to 216,000 fluid particles but after introducing rendering this drops to 27,000 particles with the rendering taking up the majority of the frame time in both techniques. We find that the most significant limiting factor to splatting performance to be the onscreen area occupied by fluid while the raycasting performance is primarily determined by the resolution of the 3D texture used for sampling. Finally we find that performing solid interaction on the CPU is a viable approach that does not introduce significant overhead unless solid particles vastly outnumber fluid ones

Animating jellyfish through numerical simulation and symmetry exploitation

This thesis presents an automatic animation system for jellyfish that is based on a physical simulation of the organism and its surrounding fluid. Our goal is to explore the unusual style of locomotion, namely jet propulsion, which is utilized by jellyfish. The organism achieves this propulsion by contracting its body, expelling water, and propelling itself forward. The organism then expands again to refill itself with water for a subsequent stroke. We endeavor to model the thrust achieved by the jellyfish, and also the evolution of the organism's geometric configuration. We restrict our discussion of locomotion to fully grown adult jellyfish, and we restrict our study of locomotion to the resonant gait, which is the organism's most active mode of locomotion, and is characterized by a regular contraction rate that is near one of the creature's resonant frequencies. We also consider only species that are axially symmetric, and thus are able to reduce the dimensionality of our model. We can approximate the full 3D geometry of a jellyfish by simulating a 2D slice of the organism. This model reduction yields plausible results at a lower computational cost. From the 2D simulation, we extrapolate to a full 3D model. To prevent our extrapolated model from being artificially smooth, we give the final shape more variation by adding noise to the 3D geometry. This noise is inspired by empirical data of real jellyfish, and also by work with continuous noise functions from the graphics community. Our 2D simulations are done numerically with ideas from the field of computational fluid dynamics. Specifically, we simulate the elastic volume of the jellyfish with a spring-mass system, and we simulate the surrounding fluid using the semi-Lagrangian method. To couple the particle-based elastic representation with the grid-based fluid representation, we use the immersed boundary method. We find this combination of methods to be a very efficient means of simulating the 2D slice with a minimal compromise in physical accuracy

Discrete Differential Geometry and Physics of Elastic Curves

We develop a general computational model for a elastic rod which allows for extension and shear.Physic