Chain Shape Matching for Simulating Complex Hairstyles

Animations of hair dynamics greatly enrich the visual attractiveness of human characters. Traditional simulation techniques handle hair as clumps or continuum for efficiency; however, the visual quality is limited because they cannot represent the fine‐scale motion of individual hair strands. Although a recent mass‐spring approach tackled the problem of simulating the dynamics of every strand of hair, it required a complicated setting of springs and suffered from high computational cost. In this paper, we base the animation of hair on such a fine‐scale on Lattice Shape Matching (LSM), which has been successfully used for simulating deformable objects. Our method regards each strand of hair as a chain of particles, and computes geometrically derived forces for the chain based on shape matching. Each chain of particles is simulated as an individual strand of hair. Our method can easily handle complex hairstyles such as curly or afro styles in a numerically stable way. While our method is not physically based, our GPU‐based simulator achieves visually plausible animations consisting of several tens of thousands of hair strands at interactive rates.     

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.     

Wetting Effects in Hair Simulation

There is considerable recent progress in hair simulations, driven by the high demands in computer animated movies. However, capturing the complex interactions between hair and water is still relatively in its infancy. Such interactions are best modeled as those between water and an anisotropic permeable medium as water can flow into and out of the hair volume biased in hair fiber direction. Modeling the interaction is further challenged when the hair is allowed to move. In this paper, we introduce a simulation model that reproduces interactions between water and hair as a dynamic anisotropic permeable material. We utilize an Eulerian approach for capturing the microscopic porosity of hair and handle the wetting effects using a Cartesian bounding grid. A Lagrangian approach is used to simulate every single hair strand including interactions with each other, yielding fine‐detailed dynamic hair simulation. Our model and simulation generate many interesting effects of interactions between fine‐detailed dynamic hair and water, i.e., water absorption and diffusion, cohesion of wet hair strands, water flow within the hair volume, water dripping from the wet hair strands and morphological shape transformations of wet hair.     

Model reference robust adaptive control for a class of uncertain switched linear systems

In this paper, we proposed a model reference robust adaptive control approach for a class of uncertain switched linear systems, in which subsystems of the switched linear system are in control canonical form. The control architecture is composed of a switched reference system (SRS) and a switched adaptive controller (SAC). The SRS specifies the desired dynamics of the uncertain switched linear system, while the SAC makes the uncertain switched linear system dynamics track the SRS dynamics. By multiple Lyapunov functions method, we prove that the closed‐loop switched system is uniformly bounded under arbitrary switching laws, provided that a linear matrix inequality (LMI)‐based sufficient condition is satisfied. We apply the proposed approach to a typical servo‐hydraulic positioning system. The simulation results show that the proposed approach is fairly insensitive to disturbances, uncertainties and non‐smoothly varying dynamics, and performs better than a proportional‐derivative controller or a minimal controller synthesis controller. Copyright © 2011 John Wiley & Sons, Ltd.     

Motion Panoramas

In this paper we describe a method for analysing video sequences and for representing them as mosaics or panoramas. Previous work on video mosaicking essentially concentrated on static scenes. We generalize these approaches to the case of a rotating camera observing both static and moving objects where the static portions of the scene are not necessarily dominant, as it has been often hypothesized in the past. We start by describing a robust technique for accurately aligning a large number of video frames under unknown camera rotations and camera settings. The alignment technique combines a feature‐based method (initialization and refinement) with rough motion segmentation followed by a colour‐based direct method (final adjustment). This precise frame‐to‐frame alignment allows the dynamic building of a background representation as well as an efficient segmentation of each image such that moving regions of arbitrary shape and size are aligned with the static background. Thus a motion panorama visualizes both dynamic and static scene elements in a geometrically consistent way. Extensive experiments applied to archived videos of track‐and‐field events validate the approach. Copyright © 2004 John Wiley & Sons, Ltd.     

Simulation‐Ready Hair Capture

Physical simulation has long been the approach of choice for generating realistic hair animations in CG. A constant drawback of simulation, however, is the necessity to manually set the physical parameters of the simulation model in order to get the desired dynamic behavior. To alleviate this, researchers have begun to explore methods for reconstructing hair from the real world and even to estimate the corresponding simulation parameters through the process of inversion. So far, however, these methods have had limited applicability, because dynamic hair capture can only be played back without the ability to edit, and solving for simulation parameters can only be accomplished for static hairstyles, ignoring the dynamic behavior. We present the first method for capturing dynamic hair and automatically determining the physical properties for simulating the observed hairstyle in motion. Since our dynamic inversion is agnostic to the simulation model, the proposed method applies to virtually any hair simulation technique, which we demonstrate using two state‐of‐the‐art hair simulation models. The output of our method is a fully simulation‐ready hairstyle, consisting of both the static hair geometry as well as its physical properties. The hairstyle can be easily edited by adding additional external forces, changing the head motion, or re‐simulating in completely different environments, all while remaining faithful to the captured hairstyle.     

A Practical and Controllable Hair and Fur Model for Production Path Tracing

We present an energy‐conserving fiber shading model for hair and fur that is efficient enough for path tracing. Our model adopts a near‐field formulation to avoid the expensive integral across the fiber, accounts for all high order internal reflection events with a single lobe, and proposes a novel, closed‐form distribution for azimuthal roughness based on the logistic distribution. Additionally, we derive, through simulation, a parameterization that relates intuitive user controls such as multiple‐scattering albedo and isotropic cylinder roughness to the underlying physical parameters.     

Semantic context based refinement for news video annotation

Automatic video annotation is to bridge the semantic gap and facilitate concept based video retrieval by detecting high level concepts from video data. Recently, utilizing context information has emerged as an important direction in such domain. In this paper, we present a novel video annotation refinement approach by utilizing extrinsic semantic context extracted from video subtitles and intrinsic context among candidate annotation concepts. The extrinsic semantic context is formed by identifying a set of key terms from video subtitles. The semantic similarity between those key terms and the candidate annotation concepts is then exploited to refine initial annotation results, while most existing approaches utilize textual information heuristically. Similarity measurements including Google distance and WordNet distance have been investigated for such a refinement purpose, which is different with approaches deriving semantic relationship among concepts from given training datasets. Visualness is also utilized to discriminate individual terms for further refinement. In addition, Random Walk with Restarts (RWR) technique is employed to perform final refinement of the annotation results by exploring the inter-relationship among annotation concepts. Comprehensive experiments on TRECVID 2005 dataset have been conducted to demonstrate the effectiveness of the proposed annotation approach and to investigate the impact of various factors.     

Hair Modeling and Simulation by Style

As the deformation behaviors of hair strands vary greatly depending on the hairstyle, the computational cost and accuracy of hair movement simulations can be significantly improved by applying simulation methods specific to a certain style. This paper makes two contributions with regard to the simulation of various hair styles. First, we propose a novel method to reconstruct simulatable hair strands from hair meshes created by artists. Manually created hair meshes consist of numerous mesh patches, and the strand reconstruction process is challenged by the absence of connectivity information among the patches for the same strand and the omission of hidden parts of strands due to the manual creation process. To this end, we develop a two‐stage spectral clustering method for estimating the degree of connectivity among patches and a strand‐growing method that preserves hairstyles. Next, we develop a hairstyle classification method for style‐specific simulations. In particular, we propose a set of features for efficient classifications and show that classifiers trained with the proposed features have higher accuracy than those trained with naive features. Our method applies efficient simulation methods according to the hairstyle without specific user input, and thus is favorable for real‐time simulation.     

Neural critic learning toward robust dynamic stabilization

In this article, we focus on developing a neural‐network‐based critic learning strategy toward robust dynamic stabilization for a class of uncertain nonlinear systems. A type of general uncertainties involved both in the internal dynamics and in the input matrix is considered. An auxiliary system with actual action and auxiliary signal is constructed after dynamics decomposition and combination for the original plant. The reasonability of the control problem transformation from robust stabilization to optimal feedback design is also provided theoretically. After that, the adaptive critic learning method based on a neural network is established to derive the approximate optimal solution of the transformed control problem. The critic weight can be initialized to a zero vector, which apparently facilitates the learning process. Numerical simulation is finally presented to illustrate the effectiveness of the critic learning approach for neural robust stabilization.     

An optimal constrained approach for divergence-free velocity interpolation and multilevel VOF method

The use of mesh refinement techniques is becoming more and more popular in computational fluid dynamics, from multilevel approaches to adaptive mesh refinement. In this paper we present a new method to interpolate the coarse velocity field which is based on an optimal approach and is characterized by a constrained minimization of an objective functional. The functional contains the sum of the square difference between the velocity components and their target average value subject to a number of divergence-free constraints. In this work we describe this approach in two- and three-dimensional geometries with different discrete velocity field configurations. This technique is applied to a multilevel Volume-of-Fluid (VOF) method where the volume fraction function is used to reconstruct and advect the interface between two immiscible phases. The coarse velocity field is interpolated to a fixed fine grid with the optimal approach over a given number of refinement levels. The results of several kinematic tests are presented, where the mass and geometrical errors are compared with those obtained with refined velocity fields interpolated with a simple midpoint rule.     

Real‐time cutting simulation of meshless deformable object using dynamic bounding volume hierarchy

This paper proposes a novel method for a real‐time cutting simulation of deformable objects using meshless method. The method utilizes a rapid refinement of topological relations among the simulation nodes of meshless deformable objects. Topological relations are defined as an undirected graph based on a visibility criterion. The graph connects the adjacent nodes that lie within a support of each node. The topological relations are refined by removing the edges of the graph that is intersected by the cut surface during the cutting simulation. Our approach utilizes a bounding volume hierarchy (BVH) to accelerate the computation of the intersection test. The BVH reconstruction algorithm is proposed to account for the cases where pieces of the object are completely cut out from the object. Algorithms to examine the connectivity among simulation nodes and accordingly reconstructing the BVH using two‐level BVH are presented. The proposed approach achieves real‐time cutting simulation of deformable objects through the rapid refinement of the topological relation. In addition, the computational performance of the cutting procedure is preserved during the entire simulation, thanks to the real‐time reconstruction of the BVH. Copyright © 2012 John Wiley & Sons, Ltd.     

HMM based soccer video event detection using enhanced mid-level semantic

Highlight detection is a fundamental step in semantics based video retrieval and personalized sports video browsing. In this paper, an effective hidden Markov models (HMMs) based soccer video event detection method based on a hierarchical video analysis framework is proposed. Soccer video shots are classified into four coarse mid-level semantics: global, median, close-up and audience. Global and local motion information is utilized for the refinement of coarse mid-level semantics. Sequential soccer video is segmented into event clips. Both the temporal transitions of the mid-level semantics and the overall features of an event clip are fused using HMMs to determine the type of event. Highlight detection performance of dynamic Bayesian networks (DBN), conditional random fields (CRF) and the proposed HMM based approach are compared. The average F-score of our highlights (including goal, shoot, foul and placed kick) detection approach is 82.92%, which outperforms that of DBN and CRF by 9.85% and 11.12% respectively. The effects of number of hidden states, overall features, and the refinement of mid-level semantics on the event detection performance are also discussed.     

Video placement and configuration of distributed video servers on cable TV networks

A large-scale, distributed video-on-demand (VOD) system allows geographically dispersed residential and business users to access video services, such as movies and other multimedia programs or documents on demand from video servers on a high-speed network. In this paper, we first demonstrate through analysis and simulation the need for a hierarchical architecture for the VOD distribution network.We then assume a hierarchical architecture, which fits the existing tree topology used in today's cable TV (CATV) hybrid fiber/coaxial (HFC) distribution networks. We develop a model for the video program placement, configuration, and performance evaluation of such systems. Our approach takes into account the user behavior, the fact that the user requests are transmitted over a shared channel before reaching the video server containing the requested program, the fact that the input/output (I/O) capacity of the video servers is the costlier resource, and finally the communication cost. In addition, our model employs batching of user requests at the video servers. We study the effect of batching on the performance of the video servers and on the quality of service (QoS) delivered to the user, and we contribute dynamic batching policies which improve server utilization, user QoS, and lower the servers' cost. The evaluation is based on an extensive analytical and simulation study.     

Calculating upward and downward simulations of state-based specifications

This paper concerns calculational methods of refinement in state-based specification languages. Data refinement is a well-established technique for transforming specifications of abstract data types into ones, which are closer to an eventual implementation. The conditions under which a transformation is a correct refinement are encapsulated into two simulation rules: downward and upward simulations.One approach for refining an abstract system is to specify the concrete data type, and then attempt to verify that it is a valid refinement of the abstract type. An alternative approach is to calculate the concrete specification based upon the abstract specification and a retrieve relation, which links the abstract and concrete states. In this paper we generalise existing calculational methods for downward simulations and derive similar results for upward simulations; we also document their use and application in a particular specification language, namely Z.     

Physically Based Deformable Models in Computer Graphics

Physically based deformable models have been widely embraced by the Computer Graphics community. Many problems outlined in a previous survey by Gibson and Mirtich have been addressed, thereby making these models interesting and useful for both offline and real‐time applications, such as motion pictures and video games. In this paper, we present the most significant contributions of the past decade, which produce such impressive and perceivably realistic animations and simulations: finite element/difference/volume methods, mass‐spring systems, mesh‐free methods, coupled particle systems and reduced deformable models‐based on modal analysis. For completeness, we also make a connection to the simulation of other continua, such as fluids, gases and melting objects. Since time integration is inherent to all simulated phenomena, the general notion of time discretization is treated separately, while specifics are left to the respective models. Finally, we discuss areas of application, such as elastoplastic deformation and fracture, cloth and hair animation, virtual surgery simulation, interactive entertainment and fluid/smoke animation, and also suggest areas for future research.     

OpenGL中模拟目标与实时场景的融合技术

为了使视景仿真达到实时性和逼真性的双重要求,介绍了一种基于实时视频的真实背景与仿真模型进行融合的仿真场景实现技术.使用视频应用程序软件工具包VFW(Video for Windows)捕获实时视频形成真实纹理,在OpenGL仿真系统中将真实纹理代替传统的三维背景建模,建立了飞机在高空俯视地面的具有层次变化的仿真场景.实验证明这种方法不但简化了视景仿真步骤,节省了背景建模时间,而且增加了逼真度,易于实现场景的快速仿真.     

A subspace approach to balanced truncation for model reduction of nonlinear control systems

In this paper, we introduce a new method of model reduction for nonlinear control systems. Our approach is to construct an approximately balanced realization. The method requires only standard matrix computations, and we show that when it is applied to linear systems it results in the usual balanced truncation. For nonlinear systems, the method makes use of data from either simulation or experiment to identify the dynamics relevant to the input–output map of the system. An important feature of this approach is that the resulting reduced‐order model is nonlinear, and has inputs and outputs suitable for control. We perform an example reduction for a nonlinear mechanical system. Copyright © 2002 John Wiley & Sons, Ltd.     

Generation of augmented video sequences combining behavioral animation and multi‐object tracking

In this paper we present a novel approach to generate augmented video sequences in real‐time, involving interactions between virtual and real agents in real scenarios. On the one hand, real agent motion is estimated by means of a multi‐object tracking algorithm, which determines real objects' position over the scenario for each time step. On the other hand, virtual agents are provided with behavior models considering their interaction with the environment and with other agents. The resulting framework allows to generate video sequences involving behavior‐based virtual agents that react to real agent behavior and has applications in education, simulation, and in the game and movie industries. We show the performance of the proposed approach in an indoor and outdoor scenario simulating human and vehicle agents. Copyright © 2009 John Wiley & Sons, Ltd.