火焰动画快速模拟的新方法

针对火焰动画难以快速建模和绘制的问题,提出了完全利用GPU过程化生成火焰动画的高效算法。先用建模工具在预处理阶段构建一个由平面正方形组成的三维模型,在绘制阶段通过GPU编程对这些方形进行Billboard方式的变换,并用一些简单公式对他们的运动方式、大小和颜色来用过程化方式进行控制,最后通过alpha混合得到最终结果。算法完全在GPU里实现,能满足实时的绘制要求。     

A shading model for cloth objects

A fundamental light reflection model that takes into account the internal structure of cloth to render the peculiar gloss of cloth objects is presented. In developing this model, the microscopic structure of textiles was considered. The model represents fabric features such as fiber's cross-sectional shape or weave. By measuring the reflected light intensity from actual cloth objects of several typical materials, it was verified that the model can express the properties of several kinds of cloth, and the parameters in the model were defined     

A deformable surface model for real-time water drop animation

A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.     

A model for human faces that allows speech synchronized animation

A parametric model for human faces is described which is capable of expression and lip animation. With this model speech synchronized animation is reduced to varying parameters in accordance with a timed speech sequence.     

Linear-nonlinear neuronal model for shape from shading

The goal of shape from shading (SFS) is to recover a relative depth map from the variations of image intensity associated to changes in surface shape. There have been very few attempts at developing biologically plausible solutions to this problem, and a sound neurophysiological basis is still missing. Here we present a biologically inspired approach to SFS, formulated in terms of the well-known linear-nonlinear model of neuronal responses. Without resorting to the image irradiance equation, which is at the heart of the traditional SFS algorithms, we submit the input image to a linear filter followed by nonlinear transformations modelled on the tuning curves of the disparity-selective binocular neurons. This yields plausible shape estimates, without requiring information regarding surface reflectance or illumination.     

A fast and stable penalty method for rigid body simulation

Two methods have been used extensively to model resting contact for rigid body simulation. The first approach, the penalty method, applies virtual springs to surfaces in contact to minimize interpenetration. This method, as typically implemented, results in oscillatory behavior and considerable penetration. The second approach, based on formulating resting contact as a linear complementarity problem, determines the resting contact forces analytically to prevent interpenetration. The analytical method exhibits expected-case polynomial complexity in the number of contact points, and may fail to find a solution in polynomial time when friction is modeled. We present a fast penalty method that minimizes oscillatory behavior and leads to little penetration during resting contact; our method compares favorably to the analytical method with regard to these two measures, while exhibiting much faster performance both asymptotically and empirically.     

A two-level generative model for cloth representation and shape from shading

In this paper, we present a two-level generative model for representing the images and surface depth maps of drapery and clothes. The upper level consists of a number of folds which will generate the high contrast (ridge) areas with a dictionary of shading primitives (for 2D images) and fold primitives (for 3D depth maps). These primitives are represented in parametric forms and are learned in a supervised learning phase using 3D surfaces of clothes acquired through photometric stereo. The lower level consists of the remaining flat areas which fill between the folds with a smoothness prior (Markov random field). We show that the classical ill-posed problem-shape from shading (SFS) can be much improved by this two-level model for its reduced dimensionality and incorporation of middle-level visual knowledge, i.e., the dictionary of primitives. Given an input image, we first infer the folds and compute a sketch graph using a sketch pursuit algorithm as in the primal sketch (Guo et al., 2003). The 3D folds are estimated by parameter fitting using the fold dictionary and they form the "skeleton" of the drapery/cloth surfaces. Then, the lower level is computed by conventional SFS method using the fold areas as boundary conditions. The two levels interact at the final stage by optimizing a joint Bayesian posterior probability on the depth map. We show a number of experiments which demonstrate more robust results in comparison with state-of-the-art work. In a broader scope, our representation can be viewed as a two-level inhomogeneous MRF model which is applicable to general shape-from-X problems. Our study is an attempt to revisit Marr's idea (Marr and Freeman, 1982) of computing the 2frac12D sketch from primal sketch. In a companion paper (Barbu and Zhu, 2005), we study shape from stereo based on a similar two-level generative sketch representation.     

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。     

A fast algorithm for computing moments of gray images based on NAM and extended shading approach

Computing moments on images is very important in the fields of image processing and pattern recognition. The non-symmetry and anti-packing model (NAM) is a general pattern representation model that has been developed to help design some efficient image representation methods. In this paper, inspired by the idea of computing moments based on the S-Tree coding (STC) representation and by using the NAM and extended shading (NAMES) approach, we propose a fast algorithm for computing lower order moments based on the NAMES representation, which takes O(N) time where N is the number of NAM blocks. By taking three idiomatic standard gray images ‘Lena’, ‘F16’, and ‘Peppers’ in the field of image processing as typical test objects, and by comparing our proposed algorithm with the conventional algorithm and the popular STC representation algorithm for computing the lower order moments, the theoretical and experimental results presented in this paper show that the average execution time improvement ratios of the proposed NAMES approach over the STC approach, and also the conventional approach are 26.63%, and 82.57% respectively while maintaining the image quality.     

A model for the three-dimensional reconstruction and animation of the human heart

This paper presents a strategy for the production of a computer-generated film showing the complete motion of a human heart. The model for construction and animation is discussed. The heart is decomposed into different parts; each part is considered as a subactor of the heart which is viewed as the main actor. The left ventricle simulation is emphasized, because it is based on medical measures. The atrium simulation is based on beta-spline surfaces and blood volume considerations.     

A low-cost photorealistic CG dataset rendering pipeline for facial landmark localization

Multimedia Tools and Applications - Face analysis has been a hot research field in computer vision for decades. The dataset is of vital importance for modern machine learning methods. The paper...     

A fast hybrid computation model for rectum deformation

It is a challenging task to realistically reproduce the complex deformation of soft bio-tissues in a surgical operation, especially when large deformations and movements exist. A hybrid model which we call the beads-on-string model is presented to handle the deformation and collision of the rectum in a virtual surgery simulation system. Specially tailored for this purpose, our model takes multiple layers to capture the dynamics of the rectum in an efficient manner. Inspired by the shape similarity between a rectum with regular bulges and a string of beads, we use a Cosserat rod model, coinciding with the centreline of the rectum, to calculate its deformation subject to external forces. We introduce rigid spheres, analogy to beads, moving along with the rod to approximate the shape of the rectum in handling collision. In addition, the beads (rigid spheres) provide a natural interlayer to map the deformation of the centreline to the associated mesh which presents detailed geometry of the rectum. Our approach is carefully crafted to achieve high computational efficiency and its multi-layer structure is designed to reproduce the physics of the deformation of the rectum.     

A fast stable sorting algorithm with absolutely minimum storage

An algorithm is described which sorts n numbers in place with the property of stability, i.e., preserving the original order of equal elements. The algorithm requires absolutely minimum storage 0 (log₂n) bits for program variables and a computation time at most 0 (n (log₂n)²).     

A fast and stable facial interface using integral projections

Integral projections are a useful technique in many computer vision problems. In this paper, we present a perceptual interface which allows us to navigate through a virtual 3D world by using the movements of the face of human users. The system applies advanced computer vision techniques to detect, track, and estimate the pose of the user’s head. The core of the proposed approach consists of a face tracker, which is based on the computation, alignment, and analysis of integral projections. This technique provides a robust, accurate, and stable 2D location of the face in each frame of the input video. Then, 3D location and orientation of the head are estimated, using some predefined heuristics. Finally, the resulting 3D pose is transformed into control signals for the navigation in the virtual world. The proposed approach has been implemented and tested in a prototype, which is publicly available. Some experimental results are shown, proving the feasibility of the method. The perceptual interface is fast, stable, and robust to facial expression and illumination conditions.     

An fast simulation tool for fluid animation in VR application based on GPUs

Multimedia Tools and Applications - Realistic and real-time simulation of fluid animation is widely used to the application of virtual reality(VR) such as VR game, special effect in film, augmented...     

A generative sketch model for human hair analysis and synthesis

In this paper, we present a generative sketch model for human hair analysis and synthesis. We treat hair images as 2D piecewise smooth vector (flow) fields and, thus, our representation is view-based in contrast to the physically-based 3D hair models in graphics. The generative model has three levels. The bottom level is the high-frequency band of the hair image. The middle level is a piecewise smooth vector field for the hair orientation, gradient strength, and growth directions. The top level is an attribute sketch graph for representing the discontinuities in the vector field. A sketch graph typically has a number of sketch curves which are divided into 11 types of directed primitives. Each primitive is a small window (say 5 /spl times/ 7 pixels) where the orientations and growth directions are defined in parametric forms, for example, hair boundaries, occluding lines between hair strands, dividing lines on top of the hair, etc. In addition to the three level representation, we model the shading effects, i.e., the low-frequency band of the hair image, by a linear superposition of some Gaussian image bases and we encode the hair color by a color map. The inference algorithm is divided into two stages: 1) We compute the undirected orientation field and sketch graph from an input image and 2) we compute the hair growth direction for the sketch curves and the orientation field using a Swendsen-Wang cut algorithm. Both steps maximize a joint Bayesian posterior probability. The generative model provides a straightforward way for synthesizing realistic hair images and stylistic drawings (rendering) from a sketch graph and a few Gaussian bases. The latter can be either inferred from a real hair image or input (edited) manually using a simple sketching interface. We test our algorithm on a large data set of hair images with diverse hair styles. Analysis, synthesis, and rendering results are reported in the experiments.     

A novel high-speed neural model for fast pattern recognition

Neural networks have shown good results for detecting a certain pattern in a given image. In this paper, faster neural networks for pattern detection are presented. Such processors are designed based on cross-correlation in the frequency domain between the input matrix and the input weights of neural networks. This approach is developed to reduce the computation steps required by these faster neural networks for the searching process. The principle of divide and conquer strategy is applied through matrix decomposition. Each matrix is divided into smaller in size sub-matrices and then each one is tested separately using a single faster neural processor. Furthermore, faster pattern detection is obtained using parallel processing techniques to test the resulting submatrices at the same time using the same number of faster neural networks. In contrast to faster neural networks, the speed up ratio is increased with the size of the input matrix when using faster neural networks and matrix decomposition. Moreover, the problem of local sub-matrix normalization in the frequency domain is solved. The effect of matrix normalization on the speed up ratio of pattern detection is discussed. Simulation results show that local sub-matrix normalization through weight normalization is faster than sub-matrix normalization in the spatial domain. The overall speed up ratio of the detection process is increased as the normalization of weights is done off line.     

A framework for interactive responsive animation

The availability of high‐performance 3D workstations has increased the range of application for interactive real‐time animation. In these applications the user can directly interact with the objects in the animation and direct the evolution of their motion, rather than simply watching a pre‐computed animation sequence. Interactive real‐time animation has fast‐growing applications in virtual reality, scientific visualization, medical training and distant learning. Traditional approaches to computer animation have been based on the animator having complete control over all aspects of the motion. In interactive animation the user can interact with any of the objects, which changes the current motion path or behaviour in real time. The objects in the animation must be capable of reacting to the user's actions and not simply replay a canned motion sequence. This paper presents a framework for interactive animation that allows the animator to specify the reactions of objects to events generated by other objects and the user. This framework is based on the concept of relations that describe how an object reacts to the influence of a dynamic environment. Each relation specifies one motion primitive triggered by either its enabling condition or the state of the environment. A collection of the relations is structured through several hierarchical layers to produce responsive behaviours and their variations. This framework is illustrated by several room‐based dancing examples that are modelled by relations. Copyright © 2000 John Wiley & Sons, Ltd.     

A stable bilinear element for the Reissner-Mindlin plate model

In this paper, we introduce a new quadrilateral element using isoparametric bilinear basis functions for both components of the rotation vector and the deflection. The element is a stable modification of the MITC4 element. We report on calculations with this new element, the original MITC4 and also the bilinear element, with selective reduced integration. The numerical results are in accordance with the results of the numerical analysis and they show that (i) the method with reduced integration is highly unreliable and cannot be recommended; (ii) the MITC4 performs rather well, but its instability can lead to a decrease in accuracy for the deflection and especially to an inaccurate and oscillating shear force; (iii) the drawbacks of the MITC4 are not present in the modified method.     

A temporally adaptive classifier for multispectral imagery

This paper presents a new temporally adaptive classification system for multispectral images. A spatial-temporal adaptation mechanism is devised to account for the changes in the feature space as a result of environmental variations. Classification based upon spatial features is performed using Bayesian framework or probabilistic neural networks (PNNs) while the temporal updating takes place using a spatial-temporal predictor. A simple iterative updating mechanism is also introduced for adjusting the parameters of these systems. The proposed methodology is used to develop a pixel-based cloud classification system. Experimental results on cloud classification from satellite imagery are provided to show the usefulness of this system.