基于物理模型的人脸表情动画技术研究

用计算机建立人脸表情动画是当前计算机图形学研究领域的一个富有挑战性的课题，该文在总结了国内外有关该课题研究方法的基础上，提出了一种基于物理模型的人脸表情画生成算法，并依该算法计和开发了一个实际的人脸表情动画系统HUFACE。该算法将人的脸部模拟为一个弹性体，为使计算简化，又将人脸表面依其生理特性分为八个子块，脸部表情所产生的五官动作模拟为弹性体的形变，并建立相应的弹性形变模型，当脸部表情引起脸部各子块形变时，每个子块上的各点将发生位移，于是利用该模型计算这些点的位移量，由此获得表情动画中的每一帧画面，由于脸部动作由该形变模型控制，且计算简单，速度快，因此不需存储表情动画中的各个画面，提高了系统的效率，实验结果表明，由HUFACE系统生成的人脸表情真实，自然。     

惠普图形工作站XW6000——3D动画设计的利器

惠普图形工作站xw6000具有典型的Compaq工作站的风格。在动画领域，对工作站的性能要求非常高，由于在遇到棘手任务处理的时候，通常快速反应的性能时间上的连续性可以更好刺激创作灵感，因此具有一台性能优良的工作站十分必要。HP Workstation xw6000采用了2个Intel Xeon^TM 2．8GHz处理器。     

CIMS Network Protocol and Its Net Models

Computer communication network architectures for cims are based on the OSI Reference Model.In this paper,CIMS network protocol model is set up on the basis of the corresqonding service model.Then the authors present a formal specification of transport protocols by using an extended Predicate/Transition net system that is briefly introduced in the third part.Finally,the general methods for the Petri nets based formal specification of CIMS network protocols are outlined.     

Center-Distance Continuous Probability Models and the Distance Measure

In this paper,a new statistic model named Center-Distance Continuous Probability Model(CDCPM)for speech recognition is described,which is based on Center-Distance Normal(CDN)distribution.In a CDCPM,the probability transition matrix is omitted,and the observation probability density function(PDF)in each state is in the form of embedded multiple-model(EMM)based on the Nearest Neighbour rule.The experimental results on two giant real-world Chinese speech databases and a real-world continuous-manner 2000 phrase system show that this model is a powerful one.Also,a distance measure for CDPMs is proposed which is based on the Bayesian minimum classification error(MCE) discrimination.     

使用Erwin进行数据库设计

本文首先筒单介绍数据库设计的基本形式和使用Erwin建立数据库的逻辑模型和物理模型的方法和流程。使用ERwin建模工具自动生成、更改和分析IDEF1X模型,可以实现从IDEF1X模型到数据物理设计的转变,从而提高数据库设计的质量和效率。     

汽车装配线的可视化仿真研究

由于装配系统仿真对象复杂以及传统仿真方法难以建立装配系统的仿真模型,因此该文提出运用面向对象的理论建立汽车装配线的可视化虚拟仿真系统.文中详细论述了实现该仿真系统的关键技术和流程,接着根据离散事件系统的特点介绍了装配仿真系统的仿真策略,最后以某汽车总装车间为例建立了装配线的可视化虚拟仿真系统.通过可视化仿真实现了车间的布局设计和生产过程的动态仿真,并依据仿真结果确定生产线的技术参数以决策生产.     

逻辑和物理模型同步变更规则研究

目前，绝大多数企业的逻辑模型和物理模型还处于一种初级的手工管理阶段，即使部分企业采用了电子化的管理，也仅局限于对逻辑模型的管理，企业很少将逻辑模型变更与物理模型变更进行同步考虑。文中通过对逻辑模型的各种变更情况进行梳理，制定了一套规则及算法并对规则和算法进行定义，保证了逻辑模型和物理模型的一致性，该规则的定义不仅方便企业对数据的管理，而且保证数据在逻辑和物理的一致性。最后将构建的规则运用到油田企业数据字典的管理中，取得了很好的应用效果。     

基于不确定性的弹性供应链的构建

本文介绍了弹性供应链的含义和特点,并讨论了供应链面临的不确定性,包括供应、生产、销售三大供应链内在不确定性和环境、竞争对手行为两大供应链外在不确定性。并在此基础上,针对性地提出了应对机制,构建了弹性供应链模型。     

数据建模与数据库设计

本文从数据建模的角度探讨了数据库的技术和方法,阐述了如何通过数据建模技术设计一致的、可共享的数据库,以降低系统开发和维护的成本。重点描述了采用ＩＤＥＦ１Ｘ数据建模技术建立逻辑模型的方法和步骤,并结合Ｏｒａｃｌｅ数据库给出了通过逻辑模型建立物理模型的过程,以及实现逻辑模型中相关的业务规则的技术。     

Remeshing-free Graph-based Finite Element Method for Fracture Simulation

Fracture produces new mesh fragments that introduce additional degrees of freedom in the system dynamics. Existing finite element method (FEM) based solutions suffer from increasing computational cost as the system matrix size increases. We solve this problem by presenting a graph-based FEM model for fracture simulation that is remeshing-free and easily scales to high-resolution meshes. Our algorithm models fracture on the graph induced in a volumetric mesh with tetrahedral elements. We relabel the edges of the graph using a computed damage variable to initialize and propagate fracture. We prove that non-linear, hyper-elastic strain energy density is expressible entirely in terms of the edge lengths of the induced graph. This allows us to reformulate the system dynamics for the relabelled graph without changing the size of the system dynamics matrix and thus prevents the computational cost from blowing up. The fractured surface has to be reconstructed explicitly only for visualization purposes. We simulate standard laboratory experiments from structural mechanics and compare the results with corresponding real-world experiments. We fracture objects made of a variety of brittle and ductile materials, and show that our technique offers stability and speed that is unmatched in current literature.     

Functionality‐Driven Musculature Retargeting

We present a novel retargeting algorithm that transfers the musculature of a reference anatomical model to new bodies with different sizes, body proportions, muscle capability, and joint range of motion while preserving the functionality of the original musculature as closely as possible. The geometric configuration and physiological parameters of musculotendon units are estimated and optimized to adapt to new bodies. The range of motion around joints is estimated from a motion capture dataset and edited further for individual models. The retargeted model is simulation‐ready, so we can physically simulate muscle‐actuated motor skills with the model. Our system is capable of generating a wide variety of anatomical bodies that can be simulated to walk, run, jump and dance while maintaining balance under gravity. We will also demonstrate the construction of individualized musculoskeletal models from bi‐planar X‐ray images and medical examination.     

The Matchstick Model for Anisotropic Friction Cones

Inspired by frictional behaviour that is observed when sliding matchsticks against one another at different angles, we propose a phenomenological anisotropic friction model for structured surfaces. Our model interpolates isotropic and anisotropic elliptical Coulomb friction parameters for a pair of surfaces with perpendicular and parallel structure directions (e.g. the wood grain direction). We view our model as a special case of an abstract friction model that produces a cone based on state information, specifically the relationship between structure directions. We show how our model can be integrated into LCP and NCP-based simulators using different solvers with both explicit and fully implicit time-integration. The focus of our work is on symmetric friction cones, and we therefore demonstrate a variety of simulation scenarios where the friction structure directions play an important part in the resulting motions. Consequently, authoring of friction using our model is intuitive and we demonstrate that our model is compatible with standard authoring practices, such as texture mapping.     

Monolithic Friction and Contact Handling for Rigid Bodies and Fluids Using SPH

We propose a novel monolithic pure SPH formulation to simulate fluids strongly coupled with rigid bodies. This includes fluid incompressibility, fluid–rigid interface handling and rigid–rigid contact handling with a viable implicit particle-based dry friction formulation. The resulting global system is solved using a new accelerated solver implementation that outperforms existing fluid and coupled rigid–fluid simulation approaches. We compare results of our simulation method to analytical solutions, show performance evaluations of our solver and present a variety of new and challenging simulation scenarios.     

Accelerating Liquid Simulation With an Improved Data-Driven Method

In physics-based liquid simulation for graphics applications, pressure projection consumes a significant amount of computational time and is frequently the bottleneck of the computational efficiency. How to rapidly apply the pressure projection and at the same time how to accurately capture the liquid geometry are always among the most popular topics in the current research trend in liquid simulations. In this paper, we incorporate an artificial neural network into the simulation pipeline for handling the tricky projection step for liquid animation. Compared with the previous neural-network-based works for gas flows, this paper advocates new advances in the composition of representative features as well as the loss functions in order to facilitate fluid simulation with free-surface boundary. Specifically, we choose both the velocity and the level-set function as the additional representation of the fluid states, which allows not only the motion but also the boundary position to be considered in the neural network solver. Meanwhile, we use the divergence error in the loss function to further emulate the lifelike behaviours of liquid. With these arrangements, our method could greatly accelerate the pressure projection step in liquid simulation, while maintaining fairly convincing visual results. Additionally, our neutral network performs well when being applied to new scene synthesis even with varied boundaries or scales.     

Numerical Coarsening with Neural Shape Functions

We propose to use nonlinear shape functions represented as neural networks in numerical coarsening to achieve generalization capability as well as good accuracy. To overcome the challenge of generalization to different simulation scenarios, especially nonlinear materials under large deformations, our key idea is to replace the linear mapping between coarse and fine meshes adopted in previous works with a nonlinear one represented by neural networks. However, directly applying an end-to-end neural representation leads to poor performance due to over-huge parameter space as well as failing to capture some intrinsic geometry properties of shape functions. Our solution is to embed geometry constraints as the prior knowledge in learning, which greatly improves training efficiency and inference robustness. With the trained neural shape functions, we can easily adopt numerical coarsening in the simulation of various hyperelastic models without any other preprocessing step required. The experiment results demonstrate the efficiency and generalization capability of our method over previous works.     

Anisotropic Strain Limiting for Quadrilateral and Triangular Cloth Meshes

The cloth simulation systems often suffer from excessive extension on the polygonal mesh, so an additional strain‐limiting process is typically used as a remedy in the simulation pipeline. A cloth model can be discretized as either a quadrilateral mesh or a triangular mesh, and their strains are measured differently. The edge‐based strain‐limiting method for a quadrilateral mesh creates anisotropic behaviour by nature, as discretization usually aligns the edges along the warp and weft directions. We improve this anisotropic technique by replacing the traditionally used equality constraints with inequality ones in the mathematical optimization, and achieve faster convergence. For a triangular mesh, the state‐of‐the‐art technique measures and constrains the strains along the two principal (and constantly changing) directions in a triangle, resulting in an isotropic behaviour which prohibits shearing. Based on the framework of inequality‐constrained optimization, we propose a warp and weft strain‐limiting formulation. This anisotropic model is more appropriate for textile materials that do not exhibit isotropic strain behaviour.     

Periodic motion synthesis and Fourier compression

Periodic motion is an important class of motion to synthesize, but it is not easy to compute it robustly and efficiently. In this paper we propose a simple, robust and efficient method to compute periodic motion from linear equation systems. The method first calculates the response of the system when an external periodic force is applied during one period, and then sums up the periodically shifted versions of the system response to provide the periodic solution. It is also shown that Fourier decomposition is very effective to compress the motion data without a drop in visual fidelity. © 1998 John Wiley & Sons, Ltd.     

Turbulent Details Simulation for SPH Fluids via Vorticity Refinement

A major issue in smoothed particle hydrodynamics (SPH) approaches is the numerical dissipation during the projection process, especially under coarse discretizations. High‐frequency details, such as turbulence and vortices, are smoothed out, leading to unrealistic results. To address this issue, we introduce a vorticity refinement (VR) solver for SPH fluids with negligible computational overhead. In this method, the numerical dissipation of the vorticity field is recovered by the difference between the theoretical and the actual vorticity, so as to enhance turbulence details. Instead of solving the Biot‐Savart integrals, a stream function, which is easier and more efficient to solve, is used to relate the vorticity field to the velocity field. We obtain turbulence effects of different intensity levels by changing an adjustable parameter. Since the vorticity field is enhanced according to the curl field, our method can not only amplify existing vortices, but also capture additional turbulence. Our VR solver is straightforward to implement and can be easily integrated into existing SPH methods.     

Adaptive Physically Based Models in Computer Graphics

One of the major challenges in physically based modelling is making simulations efficient. Adaptive models provide an essential solution to these efficiency goals. These models are able to self‐adapt in space and time, attempting to provide the best possible compromise between accuracy and speed. This survey reviews the adaptive solutions proposed so far in computer graphics. Models are classified according to the strategy they use for adaptation, from time‐stepping and freezing techniques to geometric adaptivity in the form of structured grids, meshes and particles. Applications range from fluids, through deformable bodies, to articulated solids.