基于Cosserat理论的头发动态模拟*

针对基于弹性杆理论的超螺旋模型中对动力学方程的求解影响头发模拟实时性的问题,采用Cosserat弹性杆理论对头发建模,引入角速度变量,并加入头发运动平衡的固有约束,得到改进的拉格朗日动力学运动方程;然后,将头发单体离散化,用角速度和四元数作为状态变量简化动力学方程,用半显式的欧拉方程加速方程的执行,大大降低了系统的运行时间,提高了模拟的速度,在满足实时性要求的同时提高了头发模拟的真实度。     

多股螺旋扭转弹簧参数化建模方法研究

多股螺旋扭转弹簧在自动武器中广泛使用,目前仍没有一个标准的参数化建模方法。根据多股螺旋弹簧几何成形原理,分析了多股螺旋扭转弹簧中一次螺旋线和二次螺旋线函数关系,研究了多股扭簧标准三维参数化建模方法。在UG NX中,通过动态表达式建模方法,应用"扫掠"、"草图"等功能,建立了双圆柱三股螺旋扭转弹簧参数化模板,根据81式和56式7.62 mm步枪的扭簧参数进行参数化建模,验证了参数化建模的可行性。多股螺旋扭转弹簧建模过程中,采用标准的命名,为各类复杂弹簧参数化建模提供参考,推进复杂模型的三维参数化进程。     

基于超螺旋模型的头发动态模拟方法

针对现有头发模型缺乏柔性的问题,提出一种改进的基于超螺旋模型的头发建模与仿真方法,将导引发丝构造成具有有限自由度的分段螺旋体,运用拉格朗日力学对发丝运动进行计算。通过改进卷发曲率和捻度的计算方法,并采用自适应控制结构对头发进行重组和细分,提高模拟过程的准确性和稳定性。实验结果证明,该方法可以获得较为逼真的动态模拟头发的效果。     

3D头发动态效果制作全卷（上）——表现更为自然的头发向此目标发起挑战 PART ONE（1）：利用Maya表现头发的动态效果—Paint Effect

在3D动画制作业界．动画设计者们在制作自然的人物动态效果的同时．一直不断致力于头发的自然表现及相应的动画研究。事实上，表现较为写实的头发效果并不容易。在第一部分中，我们将学习Maya中的头发制作．并学习利用Paint Effect表现动画效果的方法。     

基于学习的群体动画生成技术研究

为了降低群体动画中生成大量自然而又相似的人体运动的难度和复杂性,研究了一种基于学习的群体动画生成技术。该技术首先通过建立基于高斯过程隐变量模型和隐空间动态模型的运动姿势学习模型,将高维运动姿势映射到低维隐空间中,并在低维隐空间对相邻姿势的动态演化进行建模;然后通过对已有运动数据的学习来获得组成该运动的姿势的概率分布,再通过隐空间中的动态预测和Hybrid Monte Carlo采样来得到符合给定概率分布的隐轨迹;最后通过姿势重构来得到与原运动非常相似但又不同的一系列自然的运动,以产生群体动画,从而避开了传统的基于几何和物理约束的逆运动方法固有的困难和复杂性。     

一种三维头发的仿真方法

头发的仿真一直是计算机图形学中最具挑战性的问题之一.为了得到真实感的头发图像,运用了基于NURBS曲面的头发建模方法,由悬臂梁模型在头部曲面附近生成关键头发曲线;调节控制点改变曲线形状;构造NURBS曲面四边形带代替头发簇;在头部模型对头发进行光照渲染,可以使用纹理方法映射颜色纹理和alpha纹理以生成真实头发.最后碰撞检测与响应手段增强了头发动态感.仿真结果表明,上述方法可以获得具有比较逼真效果的头发图像.     

真实感虚拟人头发动态仿真研究

针对头发的不可伸展性和数量过大造成的头发仿真时性能低效、真实感不高问题,提出一种新的头发动态仿真方法。该方法首先利用弹簧模型对单根头发进行建模,然后采用DFTL(Dynamic Follow The Leader)算法进行变形计算,并基于FTL(Static Follow The Leader)算法对头发进行快速插值,最后运用Deep Opacity Mapping技术对头发进行渲染,增强虚拟人头发的真实感。同时,对头发与头部模型、头发与头发进行碰撞检测与响应。实验结果表明,该方法生成的头发逼真自然,而且在大量渲染时保持了较高的稳定性。     

一种卡通动画中人物头发运动生成技术研究

介绍了一种新的卡通动画中人物头发运动的混合技术,使动画师们能方便地创作出有吸引力和可控性的头发运动效果,而不需要手工对头发运动表现过程进行逐帧绘制,仅设置好所需的一些关键帧画面。该技术方法演示如何根据给出的手绘卡通人物角色动作配以相应的头发运动效果。这种方法的新颖之处是,既不是简单地插入关键帧来获得头发运动效果,也不是通过物理模拟的方式来生成头发飘逸的动画,而是从动画师预先准备好的少量的作为关键帧草图的头发运动效果,建立物理模拟动画数据库,根据此数据库中头发的运动效果来创建出特定头发运动动画。此方法生成的头发动画分两个阶段完成,首先是在数据库中搜索对应的运动效果画面,然后顺利连接;其次数据库序列的关键帧之间的过渡帧由在动画中运用转移函数生成的插值补充,以实现流畅的头发飘逸动画。     

利用OSG三维图形渲染引擎实现的骨骼动画

动态实体模型是虚拟场景的重要组成部分,骨骼动画是表达虚拟场景中动态实体行为的主要技术。提出了一种虚拟场景中三维模型骨骼动画渲染的策略,即采用第三方软件建立三维动画模型,基于Cal3D动画控制机制,使用OSG三维图形渲染引擎对虚拟场景中运动的三维模型进行模拟。在VisForest软件的基础上,集成了骨骼动画渲染方法,解决了动物在虚拟地表上“踏空”的问题,扩展了动态实体在虚拟环境中的行为模拟。以梅花鹿和大象为例,逼真地模拟了动物在虚拟环境中的奔跑和行走的过程,模拟过程中动作衔接比较自然。     

基于单张图像的三维人脸建模与表情动画

在人机交互、数字娱乐等领域,传统的表情合成技术难以稳定地生成具有真实感的个性化人脸表情动画.为此,提出一种基于单张图像的三维人脸建模和表情动画系统.自动检测人脸在图像中的位置,自动定位人脸上的关键点,基于这些关键点和形变模型重建个性化三维人脸模型,对重建的人脸模型进行扩展得到完整的人脸网格,采用稀疏关键点控制的动画数据映射方法来驱动重建的人脸模型生成动态表情动画.实验结果表明,该方法稳定性强、自动化程度高,人脸模型与表情动画比较逼真.     

Linear Time Super-Helices

Thin elastic rods such as cables, phone coils, tree branches, or hair, are common objects in the real world but computing their dynamics accurately remains challenging. The recent Super-Helix model, based on the discrete equations of Kirchhoff for a piecewise helical rod, is one of the most promising models for simulating non-stretchable rods that can bend and twist. However, this model suffers from a quadratic complexity in the number of discrete elements, which, in the context of interactive applications, makes it limited to a few number of degrees of freedom - or equivalently to a low number of variations in curvature along the mean curve. This paper proposes a new, recursive scheme for the dynamics of a Super-Helix, inspired by the popular algorithm of Featherstone for serial multibody chains. Similarly to Featherstone's algorithm, we exploit the recursive kinematics of a Super-Helix to propagate elements inertias from the free end to the clamped end of the rod, while the dynamics is solved within a second pass traversing the rod in the reverse way. Besides the gain in linear complexity, which allows us to simulate a rod of complex shape much faster than the original approach, our algorithm makes it straightforward to simulate tree-like structures of Super-Helices, which turns out to be particularly useful for animating trees and plants realistically, under large displacements.     

Hybrid fur rendering: combining volumetric fur with explicit hair strands

Hair is typically modeled and rendered using either explicitly defined hair strand geometry or a volume texture of hair densities. Taken each on their own, these two hair representations have difficulties in the case of animal fur as it consists of very dense and thin undercoat hairs in combination with coarse guard hairs. Explicit hair strand geometry is not well-suited for the undercoat hairs, while volume textures are not well-suited for the guard hairs. To efficiently model and render both guard hairs and undercoat hairs, we present a hybrid technique that combines rasterization of explicitly defined guard hairs with ray marching of a prismatic shell volume with dynamic resolution. The latter is the key to practical combination of the two techniques, and it also enables a high degree of detail in the undercoat. We demonstrate that our hybrid technique creates a more detailed and soft fur appearance as compared with renderings that only use explicitly defined hair strands. Finally, our rasterization approach is based on order-independent transparency and renders high-quality fur images in seconds.     

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.     

一种头发动态模拟方法

该文提出了一种新奇的方法来表示头发,该方法建立在离散层次细节模型上,通过恰当重组和细分来表示头发。这种离散层次细节模型包括：单根头发,头发簇和头发束,通过一个基轴来控制头发的运动。基轴用四叉树数据结构来重组和细分。在运行时,通过头发的运动、头发是否可见以及与视点的距离来选择恰当的离散和连续头发层次表示。头发的碰撞检测算法是通过扫描体来快速准确交叉计算。同时,这些头发模拟和碰撞检测的方法在头发运动的整体性能和可视质量上达到一种柔性平衡。此外,该方法能够模拟不同的发型、各种头发的长度以及头发的运动。     

融合内外特征的性别分类

针对以往仅用人脸特征或头发特征来进行性别分类的片面性,提出了将两类特征相融合的性别分类方法.用对光照、尺度变化具有很强鲁棒性的Gabor小波变换提取人脸内部特征并用PCA方法降维.利用最小代价原理,将动态搜索技术用于图像空间取得头发区域,定义了头发长度、头发表面积两种外部特征,并提出了相应的特征提取方法.采用模糊神经网络对三种特征进行非线性融合.在 Essex 人脸库中进行了性别分类实验,取得了97.1%的准确率.     

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.     

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.     

基于TU动态模糊联盟合作博弈的核心及谈判集

利用模糊数学相关理论,对具有可转移效用的模糊合作博弈进行了研究,分析了TU模糊合作博弈的核心,并在此基础上对谈判集理论进行了研究,分析了谈判集与核心之间的关系。对于全联盟可能存在核心空集的情况,L-Z谈判集很好地解决了TU联盟合作博弈的收敛集问题。最后利用实例对该谈判集的有效性和可行性进行了说明。     

The Cluster Hair Model

Modeling and rendering human hair is a very challenging problem in computer graphics. The difficulty comes mainly from the amount of hair to be modeled and the fine shapes of the individual hairs. In this paper, a new cluster hair model is introduced. The new model allows the design and styling of hair to be efficiently performed at the abstract cluster level. The key idea of this work is to embed a volume density model into a generalized cylinder, which is used to specify the envelope shape of a hair cluster, so that the design and manipulation of hair can be globally and efficiently performed. The detail of the hair is then modeled by a volume density model in which a randomly generated density map on the hair base is projected into and deformed along the generalized cylinder. The main advantages of the new model are: (1) it provides a very compact and efficient representation for complex hair styles; (2) it improves significantly the feasibility of and capability for interactive hair modeling and styling; (3) it produces high quality hair images; and (4) it provides a multiresolution model for adaptive rendering. It also has the potential to support efficient dynamic simulation at the cluster level.     

基于头皮层特征点的三维头发重用方法

针对在三维头发模型重用过程中,三维头发贴合到不同的人头模型时可能会出现的错位或大小不匹配的问题,提出一种基于头皮层特征点的三维头发重用方法。首先,根据模型文件的数据存储结构,分离出头发模型的头皮层,并提取特征点;其次,结合二维平面图像人脸检测方法,对目标三维人头模型的发根范围进行了特征点提取;然后,根据两个模型的特征点计算出的平移量与缩放系数,对头发模型整体进行了平移与缩放操作;最后,单独对头皮层和人头模型的贴合进行处理。最终能够使三维头发适应目标人头模型,保证头发造型信息无丢失,而且头皮层与人头模型达到了紧密贴合的效果。实验结果表明,该方法能够有效地提高三维头发模型的重用性,并且不受头发模型个性部分和分布区域等限制。