A CNN‐based Flow Correction Method for Fast Preview

Eulerian‐based smoke simulations are sensitive to the initial parameters and grid resolutions. Due to the numerical dissipation on different levels of the grid and the nonlinearity of the governing equations, the differences in simulation resolutions will result in different results. This makes it challenging for artists to preview the animation results based on low‐resolution simulations. In this paper, we propose a learning‐based flow correction method for fast previewing based on low‐resolution smoke simulations. The main components of our approach lie in a deep convolutional neural network, a grid‐layer feature vector and a special loss function. We provide a novel matching model to represent the relationship between low‐resolution and high‐resolution smoke simulations and correct the overall shape of a low‐resolution simulation to closely follow the shape of a high‐resolution down‐sampled version. We introduce the grid‐layer concept to effectively represent the 3D fluid shape, which can also reduce the input and output dimensions. We design a special loss function for the fluid divergence‐free constraint in the neural network training process. We have demonstrated the efficacy and the generality of our approach by simulating a diversity of animations deviating from the original training set. In addition, we have integrated our approach into an existing fluid simulation framework to showcase its wide applications.     

Analysis of Long Molecular Dynamics Simulations Using Interactive Focus+Context Visualization

Analyzing molecular dynamics (MD) simulations is a key aspect to understand protein dynamics and function. With increasing computational power, it is now possible to generate very long and complex simulations, which are cumbersome to explore using traditional 3D animations of protein movements. Guided by requirements derived from multiple focus groups with protein engineering experts, we designed and developed a novel interactive visual analysis approach for long and crowded MD simulations. In this approach, we link a dynamic 3D focus+context visualization with a 2D chart of time series data to guide the detection and navigation towards important spatio‐temporal events. The 3D visualization renders elements of interest in more detail and increases the temporal resolution dependent on the time series data or the spatial region of interest. In case studies with different MD simulation data sets and research questions, we found that the proposed visual analysis approach facilitates exploratory analysis to generate, confirm, or reject hypotheses about causalities. Finally, we derived design guidelines for interactive visual analysis of complex MD simulation data.     

Uncertainty Footprint: Visualization of Nonuniform Behavior of Iterative Algorithms Applied to 4D Cell Tracking

Research on microscopy data from developing biological samples usually requires tracking individual cells over time. When cells are three‐dimensionally and densely packed in a time‐dependent scan of volumes, tracking results can become unreliable and uncertain. Not only are cell segmentation results often inaccurate to start with, but it also lacks a simple method to evaluate the tracking outcome. Previous cell tracking methods have been validated against benchmark data from real scans or artificial data, whose ground truth results are established by manual work or simulation. However, the wide variety of real‐world data makes an exhaustive validation impossible. Established cell tracking tools often fail on new data, whose issues are also difficult to diagnose with only manual examinations. Therefore, data‐independent tracking evaluation methods are desired for an explosion of microscopy data with increasing scale and resolution. In this paper, we propose the uncertainty footprint, an uncertainty quantification and visualization technique that examines nonuniformity at local convergence for an iterative evaluation process on a spatial domain supported by partially overlapping bases. We demonstrate that the patterns revealed by the uncertainty footprint indicate data processing quality in two algorithms from a typical cell tracking workflow – cell identification and association. A detailed analysis of the patterns further allows us to diagnose issues and design methods for improvements. A 4D cell tracking workflow equipped with the uncertainty footprint is capable of self diagnosis and correction for a higher accuracy than previous methods whose evaluation is limited by manual examinations.     

Real‐time Animation of Sand‐Water Interaction

Recent advances in physically‐based simulations have made it possible to generate realistic animations. However, in the case of solid‐fluid coupling, wetting effects have rarely been noticed despite their visual importance especially in interactions between fluids and granular materials. This paper presents a simple particle‐based method to model the physical mechanism of wetness propagating through granular materials; Fluid particles are absorbed in the spaces between the granular particles and these wetted granular particles then stick together due to liquid bridges that are caused by surface tension and which will subsequently disappear when over‐wetting occurs. Our method can handle these phenomena by introducing a wetness value for each granular particle and by integrating those aspects of behavior that are dependent on wetness into the simulation framework. Using this method, a GPU‐based simulator can achieve highly dynamic animations that include wetting effects in real time.     

Geometry‐Aware Framebuffer Level of Detail

This paper introduces a framebuffer level of detail algorithm for controlling the pixel workload in an interactive rendering application. Our basic strategy is to evaluate the shading in a low resolution buffer and, in a second rendering pass, resample this buffer at the desired screen resolution. The size of the lower resolution buffer provides a trade‐off between rendering time and the level of detail in the final shading. In order to reduce approximation error we use a feature‐preserving reconstruction technique that more faithfully approximates the shading near depth and normal discontinuities. We also demonstrate how intermediate components of the shading can be selectively resized to provide finer‐grained control over resource allocation. Finally, we introduce a simple control mechanism that continuously adjusts the amount of resizing necessary to maintain a target framerate. These techniques do not require any preprocessing, are straightforward to implement on modern GPUs, and are shown to provide significant performance gains for several pixel‐bound scenes.     

HairControl: A Tracking Solution for Directable Hair Simulation

We present a method for adding artistic control to physics‐based hair simulation. Taking as input an animation of a coarse set of guide hairs, we constrain a subsequent higher‐resolution simulation of detail hairs to follow the input motion in a spatially‐averaged sense. The resulting high‐resolution motion adheres to the artistic intent, but is enhanced with detailed deformations and dynamics generated by physics‐based simulation. The technical core of our approach is formed by a set of tracking constraints, requiring the center of mass of a given subset of detail hair to maintain its position relative to a reference point on the corresponding guide hair. As a crucial element of our formulation, we introduce the concept of dynamically‐changing constraint targets that allow reference points to slide along the guide hairs to provide sufficient flexibility for natural deformations. We furthermore propose to regularize the null space of the tracking constraints based on variance minimization, effectively controlling the amount of spread in the hair. We demonstrate the ability of our tracking solver to generate directable yet natural hair motion on a set of targeted experiments and show its application to production‐level animations.     

Crowd sculpting: A space‐time sculpting method for populating virtual environments

We introduce “Crowd Sculpting”: a method to interactively design populated environments by using intuitive deformation gestures to drive both the spatial coverage and the temporal sequencing of a crowd motion. Our approach assembles large environments from sets of spatial elements which contain inter‐connectible, periodic crowd animations. Such a “Crowd Patches” approach allows us to avoid expensive and difficult‐to‐control simulations. It also overcomes the limitations of motion editing, that would result into animations delimited in space and time. Our novel methods allows the user to control the crowd patches layout in ways inspired by elastic shape sculpting: the user creates and tunes the desired populated environment through stretching, bending, cutting and merging gestures, applied either in space or time. Our examples demonstrate that our method allows the space‐time editing of very large populations and results into endless animation, while offering real‐time, intuitive control and maintaining animation quality.     

Merged simulation procedure for W‐band imaging systems

This article presents and discusses a unifying simulation procedure aimed at providing more realistic performance prediction of basic imaging systems, combining 3D EM (3 Dimensions Electro‐Magnetic) simulations and nonlinear receiver circuit simulation. New methods are proposed to emulate the radiated emissivity profile of a target body and to use harmonic balance simulation to emulate nonlinear circuit/system response to a broadband noisy stimulus. The procedure focuses mainly on passive imaging, but active imaging including illuminated passive imaging is dealt with and some elemental experiments are presented and discussed for comparisons. The method enables the extrapolation of the frequency response of a single pixel detector to an array with more elements suitable for providing a complete set of pixels and can help in evaluating the most suitable bandwidth according to the operation mode (passive/active), frequency range of operation, desired resolution, and the pixel number‐image resolution tradeoff.     

Liquid Splash Modeling with Neural Networks

This paper proposes a new data‐driven approach to model detailed splashes for liquid simulations with neural networks. Our model learns to generate small‐scale splash detail for the fluid‐implicit‐particle method using training data acquired from physically parametrized, high resolution simulations. We use neural networks to model the regression of splash formation using a classifier together with a velocity modifier. For the velocity modification, we employ a heteroscedastic model. We evaluate our method for different spatial scales, simulation setups, and solvers. Our simulation results demonstrate that our model significantly improves visual fidelity with a large amount of realistic droplet formation and yields splash detail much more efficiently than finer discretizations.     

Image Synthesis for Branching Structures

We present a set of techniques for the synthesis of artificial images that depict branching structures like rivers, cracks, lightning, mountain ranges, or blood vessels. The central idea is to build a statistical model that captures the characteristic bending and branching structure from example images. Then a new skeleton structure is synthesized and the final output image is composed from image fragments of the original input images. The synthesis part of our algorithm runs mostly automatic but it optionally allows the user to control the process in order to achieve a specific result. The combination of the statistical bending and branching model with sophisticated fragment‐based image synthesis corresponds to a multi‐resolution decomposition of the underlying branching structure into the low frequency behavior (captured by the statistical model) and the high frequency detail (captured by the image detail in the fragments). This approach allows for the synthesis of realistic branching structures, while at the same time preserving important textural details from the original image.     

Psychological Evidence for Unconscious Processing of Detail in Real‐time Animation of Multiple Characters

Detailed animation of 3D articulated body models is in principle desirable but is also a highly resource‐intensive task. Resource limitations are particularly critical in 3D visualizations of multiple characters in real‐time game sequences. We investigated to what extent observers perceptually process the level of detail in naturalistic character animations. Only if such processing occurs would it be justified to spend valuable resources on richness of detail. An experiment was designed to test the effectiveness of 3D body animation. Observers had to judge the level of overall skill exhibited by four simulated soccer teams. The simulations were based on recorded RoboCup simulation league games. Thus objective skill levels were known from the teams' placement in the tournament. The animations' level of detail was varied in four increasing steps of modelling complexity. Results showed that observers failed to notice the differences in detail. Nonetheless, clear effects of character animation on perceived skill were found. We conclude that character animation co‐determines perceptual judgements even when observers are completely unaware of these manipulations. Copyright © 2000 John Wiley & Sons, Ltd.     

Automated sampling and control of gaseous simulations

In this work, we describe a method that automates the sampling and control of gaseous fluid simulations. Several recent approaches have provided techniques for artists to generate high-resolution simulations based on a low-resolution simulation. However, often in applications the overall flow in the low-resolution simulation that an animator observes and intends to preserve is composed of even lower frequencies than the low resolution itself. In such cases, attempting to match the low-resolution simulation precisely is unnecessarily restrictive. We propose a new sampling technique to efficiently capture the overall flow of a fluid simulation, at the scale of user’s choice, in such a way that the sampled information is sufficient to represent what is virtually perceived and no more. Thus, by applying control based on the sampled data, we ensure that in the resulting high-resolution simulation, the overall flow is matched to the low-resolution simulation and the fine details on the high resolution are preserved. The samples we obtain have both spatial and temporal continuity that allows smooth keyframe matching and direct manipulation of visible elements such as smoke density through temporal blending of samples. We demonstrate that a user can easily configure a simulation with our system to achieve desired results.     

A new design of delay‐dependent robust ℋ︁∞ filtering for continuous‐time polytopic systems with time‐varying delay

This paper revisits the problem of delay‐dependent robust ?_∞ filtering design for a class of continuous‐time polytopic linear systems with a time‐varying state delay. Based on a newly developed parameter‐dependent Lyapunov–Krasovskii functional combined with Projection Lemma and an improved free‐weighting matrix technique for delay‐dependent criteria, a new sufficient condition for robust ?_∞ performance analysis is first derived and then the filter synthesis is developed by using a simple matrix inequality linearization technique. It is shown that the desired filters can be constructed by solving a set of linear matrix inequalities. Finally, two simulation examples are given to show the effectiveness and less conservatism of the proposed method in comparison with the existing approaches. Copyright © 2009 John Wiley & Sons, Ltd.     

CAMA: Contact‐Aware Matrix Assembly with Unified Collision Handling for GPU‐based Cloth Simulation

We present a novel GPU‐based approach to robustly and efficiently simulate high‐resolution and complexly layered cloth. The key component of our formulation is a parallelized matrix assembly algorithm that can quickly build a large and sparse matrix in a compressed format and accurately solve linear systems on GPUs. We also present a fast and integrated solution for parallel collision handling, including collision detection and response computations, which utilizes spatio‐temporal coherence. We combine these algorithms as part of a new cloth simulation pipeline that incorporates contact forces into implicit time integration for collision avoidance. The entire pipeline is implemented on GPUs, and we evaluate its performance on complex benchmarks consisting of 100 – 300K triangles. In practice, our system takes a few seconds to simulate one frame of a complex cloth scene, which represents significant speedups over prior CPU and GPU‐based cloth simulation systems.     

Primal‐Dual Optimization for Fluids

We apply a novel optimization scheme from the image processing and machine learning areas, a fast Primal‐Dual method, to achieve controllable and realistic fluid simulations. While our method is generally applicable to many problems in fluid simulations, we focus on the two topics of fluid guiding and separating solid‐wall boundary conditions. Each problem is posed as an optimization problem and solved using our method, which contains acceleration schemes tailored to each problem. In fluid guiding, we are interested in partially guiding fluid motion to exert control while preserving fluid characteristics. With our method, we achieve explicit control over both large‐scale motions and small‐scale details which is valuable for many applications, such as level‐of‐detail adjustment (after running the coarse simulation), spatially varying guiding strength, domain modification, and resimulation with different fluid parameters. For the separating solid‐wall boundary conditions problem, our method effectively eliminates unrealistic artefacts of fluid crawling up solid walls and sticking to ceilings, requiring few changes to existing implementations. We demonstrate the fast convergence of our Primal‐Dual method with a variety of test cases for both model problems.     

Still‐Frame Simulation for Fire Effects of Images

We propose various simulation strategies to generate single‐frame fire effects for images, as opposed to multi‐frame fire effects for animations. To accelerate 3D simulation and to provide a user with early hints on the final effect, we propose a 2D‐guided 3D simulation approach, which runs a faster 2D simulation first, and then guides 3D simulation using the 2D simulation result. To achieve this, we explore various boundary conditions and develop a constrained projection method. Since only the final frame will be used while intermediate frames are abandoned, earlier intermediate frames can take larger time steps and have large noise applied, quickly generating turbulent flow structures. As the final frame approaches, we increase the flow quality by reducing the time step and not adding any noise. This adaptive time stepping allows us to use more computational resource near or at the final frame. We also develop divergence and buoyancy modification methods to guide flames along arbitrary, even physically implausible, directions. Our simulation methods can effectively and efficiently generate a variety of fire effects useful for image decoration.     

Detail‐Preserving Explicit Mesh Projection and Topology Matching for Particle‐Based Fluids

We propose a new explicit surface tracking approach for particle‐based fluid simulations. Our goal is to advect and update a highly detailed surface, while only computing a coarse simulation. Current explicit surface methods lose surface details when projecting on the isosurface of an implicit function built from particles. Our approach uses a detail‐preserving projection, based on a signed distance field, to prevent the divergence of the explicit surface without losing its initial details. Furthermore, we introduce a novel topology matching stage that corrects the topology of the explicit surface based on the topology of an implicit function. To that end, we introduce an optimization approach to update our explicit mesh signed distance field before remeshing. Our approach is successfully used to preserve the surface details of melting and highly viscous objects, and shown to be stable by handling complex cases involving multiple topological changes. Compared to the computation of a high‐resolution simulation, using our approach with a coarse fluid simulation significantly reduces the computation time and improves the quality of the resulting surface.     

改进小波多分辨力分析的数据融合算法

在小波分析中,多分辨力分析是一重要的方法。但该方法只对低频段的近似信号进行逐级细分,导致低频段频率分辨力越来越高,而高频段的细节信号保持不变,频率分辨力较低。为了克服小波多分辨力分析在高频段频率分辨力低的缺点,采用改进的小波多分辨力分析方法,由于该方法对高频段进行逐级细分,改善了小波变换在高频段的时频局部化性能,提高了小波变换高频段频率的分辨力。同时,将改进的小波多分辨力分析方法应用到多传感器数据融合中,经过仿真计算,其结果表明:该算法是有效的。     

Large and Small Eddies Matter: Animating Trees in Wind Using Coarse Fluid Simulation and Synthetic Turbulence

Animating trees in wind has long been a problem in computer graphics. Progress on this problem is important for both visual effects in films and forestry biomechanics. More generally, progress on tree motion in wind may inform future work on two‐way coupling between turbulent flows and deformable objects. Synthetic turbulence added to a coarse fluid simulation produces convincing animations of turbulent flows but two‐way coupling between the enriched flow and objects embedded in the flow has not been investigated. Prior work on two‐way coupling between fluid and deformable models lacks a subgrid resolution turbulence model. We produce realistic animations of tree motion by including motion due to both large and small eddies using synthetic subgrid turbulence and porous proxy geometry. Synthetic turbulence at the subgrid scale is modulated using turbulent kinetic energy (TKE). Adding noise after sampling the mean flow and TKE transfers energy from small eddies directly to the tree geometry. The resulting animations include both global sheltering effects and small scale leaf and branch motion. Viewers, on average, found animations, which included both coarse fluid simulation and TKE‐modulated noise to be more accurate than animations generated using coarse fluid simulation or noise alone.