Real-time Animation of Dressed Virtual Humans

In this paper, we describe a method for cloth animation in real‐time. The algorithm works in a hybrid manner exploiting the merits of both the physical‐based and geometric deformations. It makes use of predetermined conditions between the cloth and the body model, avoiding complex collision detection and physical deformations wherever possible. Garments are segmented into pieces that are simulated by various algorithms, depending on how they are laid on the body surface and whether they stick or flow on it. Tests show that the method is well suited to fully dressed virtual human models, achieving real‐time performance compared to ordinary cloth‐simulations.     

Hierarchical Deformation of Locally Rigid Meshes

We propose a method for calculating deformations of models by deforming a low‐resolution mesh and adding details while ensuring that the details we add satisfy a set of constraints. Our method builds a low‐resolution representation of a mesh by using edge collapses and performs an as‐rigid‐as‐possible deformation on the simplified mesh. We then add back details by reversing edge‐collapses so that the shape of the mesh is locally preserved. While adding details, we deform the mesh to match the predicted positions of constraints so that constraints on the full‐resolution mesh are met. Our method operates on meshes with arbitrary triangulations, satisfies constraints over the full‐resolution mesh and converges quickly.     

As‐Killing‐As‐Possible Vector Fields for Planar Deformation

Cartoon animation, image warping, and several other tasks in two‐dimensional computer graphics reduce to the formulation of a reasonable model for planar deformation. A deformation is a map from a given shape to a new one, and its quality is determined by the type of distortion it introduces. In many applications, a desirable map is as isometric as possible. Finding such deformations, however, is a nonlinear problem, and most of the existing solutions approach it by minimizing a nonlinear energy. Such methods are not guaranteed to converge to a global optimum and often suffer from robustness issues. We propose a new approach based on approximate Killing vector fields (AKVFs), first introduced in shape processing. AKVFs generate near‐isometric deformations, which can be motivated as direction fields minimizing an “as‐rigid‐as‐possible” (ARAP) energy to first order. We first solve for an AKVF on the domain given user constraints via a linear optimization problem and then use this AKVF as the initial velocity field of the deformation. In this way, we transfer the inherent nonlinearity of the deformation problem to finding trajectories for each point of the domain having the given initial velocities. We show that a specific class of trajectories — the set of logarithmic spirals — is especially suited for this task both in practice and through its relationship to linear holomorphic vector fields. We demonstrate the effectiveness of our method for planar deformation by comparing it with existing state‐of‐the‐art deformation methods.     

Sketching MLS Image Deformations On the GPU

In this paper, we present an image editing tool that allows the user to deform images using a sketch‐based interface. The user simply sketches a set of source curves in the input image, and also some target curves that the source curves should be deformed to. Then the moving least squares (MLS) deformation technique [ [SMW06] ] is adapted to produce realistic deformations while satisfying the curves' positional constraints. We also propose a scheme to reduce image fold‐overs in MLS deformations. Our system has a very intuitive user interface, generates physically plausible deformations, and can be easily implemented on the GPU for real‐time performance.     

Detail-Aware Deep Clothing Animations Infused with Multi-Source Attributes

This paper presents a novel learning-based clothing deformation method to generate rich and reasonable detailed deformations for garments worn by bodies of various shapes in various animations. In contrast to existing learning-based methods, which require numerous trained models for different garment topologies or poses and are unable to easily realize rich details, we use a unified framework to produce high fidelity deformations efficiently and easily. Specifically, we first found that the fit between the garment and the body has an important impact on the degree of folds. We then designed an attribute parser to generate detail-aware encodings and infused them into the graph neural network, therefore enhancing the discrimination of details under diverse attributes. Furthermore, to achieve better convergence and avoid overly smooth deformations, we proposed to reconstruct output to mitigate the complexity of the learning task. Experimental results show that our proposed deformation method achieves better performance over existing methods in terms of generalization ability and quality of details.     

Pose space parameterization and style transfer of skin deformation

We present a technique to parameterize skin deformation by skeletal motion and to transfer the deformation style from one character to another. We decompose skin deformation into time‐varying signals and basis matrices by using dimension reduction techniques and then approximate the time‐varying signals by using radial basis functions with respect to joint angles that define skeletal motion. This decomposition reduces the size of deformation data to a small number of time‐varying signals that represent the complex role of muscle action. The subsequent parameterization yields a fast and intuitive control of characters; thus, it allows us to construct faithful skin deformations quickly as skeletal bones move. The representation of our parameterization allows us to capture and transfer a derived deformation style to another skeleton–skin structure without considering the input dimension of the deformation data. This style transfer can be used as a basis for realistically animating variants of sample characters that have the same skeletal topology. Parameterization of skin deformation and its style transfer can be performed within a small amount of error once the preprocessing time and control of the deformation is carried out in real time by our graphics processing unit implementation. Copyright © 2011 John Wiley & Sons, Ltd.     

Automatic Cage Building with Quadric Error Metrics

Modern computer graphics applications usually require high resolution object models for realistic rendering.However,it is expensive and difficult to deform such models in real time.In order to reduce the computational cost during deformations,a dense model is often manipulated through a simplified structure,called cage,which envelops the model.However,cages are usually built interactively by users,which is tedious and time-consuming.In this paper,we introduce a novel method that can build cages automatically for both 2D polygons and 3D triangular meshes.The method consists of two steps:1) simplifying the input model with quadric error metrics and quadratic programming to build a coarse cage;2) removing the self-intersections of the coarse cage with Delaunay partitions.With this new method,a user can build a cage to envelop an input model either entirely or partially with the approximate vertex number the user specifies.Experimental results show that,compared to other cage building methods with the same number of vertex,cages built by our method are more similar to the input models.Thus,the dense models can be manipulated with higher accuracy through our cages.     

Learning object deformation models for robot motion planning

In this paper, we address the problem of robot navigation in environments with deformable objects. The aim is to include the costs of object deformations when planning the robot’s motions and trade them off against the travel costs. We present our recently developed robotic system that is able to acquire deformation models of real objects. The robot determines the elasticity parameters by physical interaction with the object and by establishing a relation between the applied forces and the resulting surface deformations. The learned deformation models can then be used to perform physically realistic finite element simulations. This allows the planner to evaluate robot trajectories and to predict the costs of object deformations. Since finite element simulations are time-consuming, we furthermore present an approach to approximate object-specific deformation cost functions by means of Gaussian process regression. We present two real-world applications of our motion planner for a wheeled robot and a manipulation robot. As we demonstrate in real-world experiments, our system is able to estimate appropriate deformation parameters of real objects that can be used to predict future deformations. We show that our deformation cost approximation improves the efficiency of the planner by several orders of magnitude.     

Learning 3D Deformation of Animals from 2D Images

Understanding how an animal can deform and articulate is essential for a realistic modification of its 3D model. In this paper, we show that such information can be learned from user‐clicked 2D images and a template 3D model of the target animal. We present a volumetric deformation framework that produces a set of new 3D models by deforming a template 3D model according to a set of user‐clicked images. Our framework is based on a novel locally‐bounded deformation energy, where every local region has its own stiffness value that bounds how much distortion is allowed at that location. We jointly learn the local stiffness bounds as we deform the template 3D mesh to match each user‐clicked image. We show that this seemingly complex task can be solved as a sequence of convex optimization problems. We demonstrate the effectiveness of our approach on cats and horses, which are highly deformable and articulated animals. Our framework produces new 3D models of animals that are significantly more plausible than methods without learned stiffness.     

Improved Model‐ and View‐Dependent Pruning of Large Botanical Scenes

We present an optimized pruning algorithm that allows for considerable geometry reduction in large botanical scenes while maintaining high and coherent rendering quality. We improve upon previous techniques by applying model‐specific geometry reduction functions and optimized scaling functions. For this we introduce the use of Precision and Recall (PR) as a measure of quality to rendering and show how PR‐scores can be used to predict better scaling values. We conducted a user‐study letting subjects adjust the scaling value, which shows that the predicted scaling matches the preferred ones. Finally, we extend the originally purely stochastic geometry prioritization for pruning to account for view‐optimized geometry selection, which allows to take global scene information, such as occlusion, into consideration. We demonstrate our method for the rendering of scenes with thousands of complex tree models in real‐time.     

Streaming 3D deforming surfaces with dynamic resolution control

Real‐time streaming of shape deformations in a shared distributed virtual environment is a challenging task due to the difficulty of transmitting large amounts of 3D animation data to multiple receiving parties at a high frame rate. In this paper, we present a framework for streaming 3D shape deformations, which allows shapes with multi‐resolutions to share the same deformations simultaneously in real time. The geometry and motion of deforming mesh or point‐sampled surfaces are compactly encoded, transmitted, and reconstructed using the spectra of the manifold harmonics. A receiver‐based multi‐resolution surface reconstruction approach is introduced, which allows deforming shapes to switch smoothly between continuous multi‐resolutions. On the basis of this dynamic reconstruction scheme, a frame rate control algorithm is further proposed to achieve rendering at interactive rates. We also demonstrate an efficient interpolation‐based strategy to reduce computing of deformation. The experiments conducted on both mesh and point‐sampled surfaces show that our approach achieves efficient performance even if deformations of complex 3D surfaces are streamed. Copyright © 2013 John Wiley & Sons, Ltd.     

基于特征线素的三维建筑表意性建模

提出了一种基于特征线素的轻量级三维建筑交互建模方法,称为Fe-Wires 方法.该方法是一种基于形状文法的过程式建模方法,通过间接地输入和操纵建筑对象的特征线条来重构模型,克服了原有基于规则的建模方法交互能力弱的缺点.为了便于对复杂建筑对象进行交互调整,给出了基于轴向弹性约束的整体形变模型.区别于传统非线性约束求解方法,该方法只需求解一个二次凸规划问题,具有很高的求解效率.实验结果表明,该方法适用于建筑室内外交互建模的实际应用.     

3D cartoon face generation by local deformation mapping

We present a data-driven method for automatically generating a 3D cartoon of a real 3D face. Given a sparse set of 3D real faces and their corresponding cartoon faces modeled by an artist, our method models the face in each subspace as the deformation of its nearby exemplars and learn a mapping between the deformations defined by the real faces and their cartoon counterparts. To reduce the exemplars needed for learning, we regress a collection of linear mappings defined locally in both face geometry and identity spaces and develop a progressive scheme for users to gradually add new exemplars for training. At runtime, our method first finds the nearby exemplars of an input real face and then constructs the result cartoon face from the corresponding cartoon faces of the nearby real face exemplars and the local deformations mapped from the real face subspace. Our method greatly simplifies the cartoon generation process by learning artistic styles from a sparse set of exemplars. We validate the efficiency and effectiveness of our method by applying it to faces of different facial features. Results demonstrate that our method not only preserves the artistic style of the exemplars, but also keeps the unique facial geometric features of different identities.     

Mesh cutting during real-time physical simulation

The ability to cut through meshes in real-time is an essential ingredient in a number of practical interactive simulations. Surgical simulation, cloth design, clay sculpting and many other related VR applications require the ability to introduce arbitrary discontinuities through models to separate, reposition, and reshape various pieces of the model as needed for the target application. In addition, in order to provide the necessary realism for these applications, model deformations must be computed from an underlying physically-based model—most commonly a continuum-based finite element model.In this work, we present a method for representing and computing, at interactive rates, the deformations of a mesh whose topology is being dynamically modified with multiple virtual tools. The method relies on introducing controlled discontinuities in the basis functions used to represent the geometry of deformation, and on fast incremental methods for updating global model deformations. The method can also generate the forces needed for force rendering in a haptic environment. The method is shown to scale well with problem size (linearly in the number of nonzeros of the Cholesky factor) allowing realistic interaction with fairly large models.     

Type‐Reduction of General Type‐2 Fuzzy Sets: The Type‐1 OWA Approach

For general type‐2 fuzzy sets, the defuzzification process is very complex and the exhaustive direct method of implementing type‐reduction is computationally expensive and turns out to be impractical. This has inevitably hindered the development of type‐2 fuzzy inferencing systems in real‐world applications. The present situation will not be expected to change, unless an efficient and fast method of deffuzzifying general type‐2 fuzzy sets emerges. Type‐1 ordered weighted averaging (OWA) operators have been proposed to aggregate expert uncertain knowledge expressed by type‐1 fuzzy sets in decision making. In particular, the recently developed alpha‐level approach to type‐1 OWA operations has proven to be an effective tool for aggregating uncertain information with uncertain weights in real‐time applications because its complexity is of linear order. In this paper, we prove that the mathematical representation of the type‐reduced set (TRS) of a general type‐2 fuzzy set is equivalent to that of a special case of type‐1 OWA operator. This relationship opens up a new way of performing type reduction of general type‐2 fuzzy sets, allowing the use of the alpha‐level approach to type‐1 OWA operations to compute the TRS of a general type‐2 fuzzy set. As a result, a fast and efficient method of computing the centroid of general type‐2 fuzzy sets is realized. The experimental results presented here illustrate the effectiveness of this method in conducting type reduction of different general type‐2 fuzzy sets.     

Elastic Correspondence between Triangle Meshes

We propose a novel approach for shape matching between triangular meshes that, in contrast to existing methods, can match crease features. Our approach is based on a hybrid optimization scheme, that solves simultaneously for an elastic deformation of the source and its projection on the target. The elastic energy we minimize is invariant to rigid body motions, and its non‐linear membrane energy component favors locally injective maps. Symmetrizing this model enables feature aligned correspondences even for non‐isometric meshes. We demonstrate the advantage of our approach over state of the art methods on isometric and non‐isometric datasets, where we improve the geodesic distance from the ground truth, the conformal and area distortions, and the mismatch of the mean curvature functions. Finally, we show that our computed maps are applicable for surface interpolation, consistent cross‐field computation, and consistent quadrangular remeshing of a set of shapes.     

Giant soap bubble creation model

We present a simple and real‐time technique for animating giant realistic looking soap bubbles. Unlike small spherical soap bubbles, giant soap bubbles stretch significantly and undergo globally varying and locally consistent deformations because of time‐varying surface tensions. For physically plausible surface tensions, we introduce and combine a variable‐length mass spring system and Gibbs elasticity and Marangoni elasticity. Using a proposed framework, we deform our models because of general forces from surface tensions, winds, and excessive pressures. Our framework effectively generates a physically plausible animation of giant soap bubbles, differing in shape according to the user's design; generates capillary waves and vibrations while floating in the air; and shows vivid iridescent colors corresponding to the deformations, all of which have been difficult to achieve using previous soap bubble animation methods. Copyright © 2015 John Wiley & Sons, Ltd.