Fast Particle‐based Visual Simulation of Ice Melting

The visual simulation of natural phenomena has been widely studied. Although several methods have been proposed to simulate melting, the flows of meltwater drops on the surfaces of objects are not taken into account. In this paper, we propose a particle‐based method for the simulation of the melting and freezing of ice objects and the interactions between ice and fluids. To simulate the flow of meltwater on ice and the formation of water droplets, a simple interfacial tension is proposed, which can be easily incorporated into common particle‐based simulation methods such as Smoothed Particle Hydrodynamics. The computations of heat transfer, the phase transition between ice and water, the interactions between ice and fluids, and the separation of ice due to melting are further accelerated by implementing our method using CUDA. We demonstrate our simulation and rendering method for depicting melting ice at interactive frame‐rates.     

Synthesizing Two‐character Interactions by Merging Captured Interaction Samples with their Spacetime Relationships

Existing synthesis methods for closely interacting virtual characters relied on user‐specified constraints such as the reaching positions and the distance between body parts. In this paper, we present a novel method for synthesizing new interacting motion by composing two existing interacting motion samples without the need to specify the constraints manually. Our method automatically detects the type of interactions contained in the inputs and determines a suitable timing for the interaction composition by analyzing the spacetime relationships of the input characters. To preserve the features of the inputs in the synthesized interaction, the two inputs will be aligned and normalized according to the relative distance and orientation of the characters from the inputs. With a linear optimization method, the output is the optimal solution to preserve the close interaction of two characters and the local details of individual character behavior. The output animations demonstrated that our method is able to create interactions of new styles that combine the characteristics of the original inputs.     

A Data‐driven Segmentation for the Shoulder Complex

The human shoulder complex is perhaps the most complicated joint in the human body being comprised of a set of three bones, muscles, tendons, and ligaments. Despite this anatomical complexity, computer graphics models for motion capture most often represent this joint as a simple ball and socket. In this paper, we present a method to determine a shoulder skeletal model that, when combined with standard skinning algorithms, generates a more visually pleasing animation that is a closer approximation to the actual skin deformations of the human body. We use a data‐driven approach and collect ground truth skin deformation data with an optical motion capture system with a large number of markers (200 markers on the shoulder complex alone). We cluster these markers during movement sequences and discover that adding one extra joint around the shoulder improves the resulting animation qualitatively and quantitatively yielding a marker set of approximately 70 markers for the complete skeleton. We demonstrate the effectiveness of our skeletal model by comparing it with ground truth data as well as with recorded video. We show its practicality by integrating it with the conventional rendering/animation pipeline.     

The Virtual Director: a Correlation‐Based Online Viewing of Human Motion

Automatic camera control for scenes depicting human motion is an imperative topic in motion capture base animation, computer games, and other animation based fields. This challenging control problem is complex and combines both geometric constraints, visibility requirements, and aesthetic elements. Therefore, existing optimization‐based approaches for human action overview are often too demanding for online computation. In this paper, we introduce an effective automatic camera control which is extremely efficient and allows online performance. Rather than optimizing a complex quality measurement, at each time it selects one active camera from a multitude of cameras that render the dynamic scene. The selection is based on the correlation between each view stream and the human motion in the scene. Two factors allow for rapid selection among tens of candidate views in real‐time, even for complex multi‐character scenes: the efficient rendering of the multitude of view streams, and optimized calculations of the correlations using modified CCA. In addition to the method's simplicity and speed, it exhibits good agreement with both cinematic idioms and previous human motion camera control work. Our evaluations show that the method is able to cope with the challenges put forth by severe occlusions, multiple characters and complex scenes.     

Non‐iterative Second‐order Approximation of Signed Distance Functions for Any Isosurface Representation

Signed distance functions (SDF) to explicit or implicit surface representations are intensively used in various computer graphics and visualization algorithms. Among others, they are applied to optimize collision detection, are used to reconstruct data fields or surfaces, and, in particular, are an obligatory ingredient for most level set methods. Level set methods are common in scientific visualization to extract surfaces from scalar or vector fields. Usual approaches for the construction of an SDF to a surface are either based on iterative solutions of a special partial differential equation or on marching algorithms involving a polygonization of the surface. We propose a novel method for a non‐iterative approximation of an SDF and its derivatives in a vicinity of a manifold. We use a second‐order algebraic fitting scheme to ensure high accuracy of the approximation. The manifold is defined (explicitly or implicitly) as an isosurface of a given volumetric scalar field. The field may be given at a set of irregular and unstructured samples. Stability and reliability of the SDF generation is achieved by a proper scaling of weights for the Moving Least Squares approximation, accurate choice of neighbors, and appropriate handling of degenerate cases. We obtain the solution in an explicit form, such that no iterative solving is necessary, which makes our approach fast.     

Interactive,Multiresolution Image‐Space Rendering for Dynamic Area Lighting

Area lights add tremendous realism, but rendering them interactively proves challenging. Integrating visibility is costly, even with current shadowing techniques, and existing methods frequently ignore illumination variations at unoccluded points due to changing radiance over the light's surface. We extend recent image‐space work that reduces costs by gathering illumination in a multiresolution fashion, rendering varying frequencies at corresponding resolutions. To compute visibility, we eschew shadow maps and instead rely on a coarse screen‐space voxelization, which effectively provides a cheap layered depth image for binary visibility queries via ray marching. Our technique requires no precomputation and runs at interactive rates, allowing scenes with large area lights, including dynamic content such as video screens.     

An Energy‐Conserving Hair Reflectance Model

We present a reflectance model for dielectric cylinders with rough surfaces such as human hair fibers. Our model is energy conserving and can evaluate arbitrarily many orders of internal reflection. Accounting for compression and contraction of specular cones produces a new longitudinal scattering function which is non‐Gaussian and includes an off‐specular peak. Accounting for roughness in the azimuthal direction leads to an integral across the hair fiber which is efficiently evaluated using a Gaussian quadrature. Solving cubic equations is avoided, caustics are included in the model in a consistent fashion, and more accurate colors are predicted by considering many internal pathways.     

Motion Retrieval Using Low‐Rank Subspace Decomposition of Motion Volume

This paper proposes a novel framework that allows for a flexible and an efficient retrieval of motion capture data in huge databases. The method first converts an action sequence into a novel representation, i.e. the Self‐Similarity Matrix (SSM), which is based on the notion of self‐similarity. This conversion of the motion sequences into compact and low‐rank subspace representations greatly reduces the spatiotemporal dimensionality of the sequences. The SSMs are then used to construct order‐3 tensors, and we propose a low‐rank decomposition scheme that allows for converting the motion sequence volumes into compact lower dimensional representations, without losing the nonlinear dynamics of the motion manifold. Thus, unlike existing linear dimensionality reduction methods that distort the motion manifold and lose very critical and discriminative components, the proposed method performs well even when inter‐class differences are small or intra‐class differences are large. In addition, the method allows for an efficient retrieval and does not require the time‐alignment of the motion sequences. We evaluate the performance of our retrieval framework on the CMU mocap dataset under two experimental settings, both demonstrating promising retrieval rates.     

Locomotion Skills for Insects with Sample‐based Controller

Natural‐looking insect animation is very difficult to simulate. The fast movement and small scale of insects often challenge the standard motion capture techniques. As for the manual key‐framing or physics‐driven methods, significant amounts of time and efforts are necessary due to the delicate structure of the insect, which prevents practical applications. In this paper, we address this challenge by presenting a two‐level control framework to efficiently automate the modeling and authoring of insects’ locomotion. On the top level, we design a Triangle Placement Engine to automatically determine the location and orientation of insects’ foot contacts, given the user‐defined trajectory and settings, including speed, load, path and terrain etc. On the low‐level, we relate the Central Pattern Generator to the triangle profiles with the assistance of a Controller Look‐Up Table to fast simulate the physically‐based movement of insects. With our approach, animators can directly author insects’ behavior among a wide range of locomotion repertoire, including walking along a specified path or on an uneven terrain, dynamically adjusting to external perturbations and collectively transporting prey back to the nest.     

Dynamic Multi‐View Exploration of Shape Spaces

Statistical shape modeling is a widely used technique for the representation and analysis of the shapes and shape variations present in a population. A statistical shape model models the distribution in a high dimensional shape space, where each shape is represented by a single point. We present a design study on the intuitive exploration and visualization of shape spaces and shape models. Our approach focuses on the dual‐space nature of these spaces. The high‐dimensional shape space represents the population, whereas object space represents the shape of the 3D object associated with a point in shape space. A 3D object view provides local details for a single shape. The high dimensional points in shape space are visualized using a 2D scatter plot projection, the axes of which can be manipulated interactively. This results in a dynamic scatter plot, with the further extension that each point is visualized as a small version of the object shape that it represents. We further enhance the population‐object duality with a new type of view aimed at shape comparison. This new “shape evolution view” visualizes shape variability along a single trajectory in shape space, and serves as a link between the two spaces described above. Our three‐view exploration concept strongly emphasizes linked interaction between all spaces. Moving the cursor over the scatter plot or evolution views, shapes are dynamically interpolated and shown in the object view. Conversely, camera manipulation in the object view affects the object visualizations in the other views. We present a GPU‐accelerated implementation, and show the effectiveness of the three‐view approach using a number of real‐world cases. In these, we demonstrate how this multi‐view approach can be used to visually explore important aspects of a statistical shape model, including specificity, compactness and reconstruction error.     

Improving Sampling‐based Motion Control

We address several limitations of the sampling‐based motion control method of Liu et at. [ LYvdP* 10 ]. The key insight is to learn from the past control reconstruction trials through sample distribution adaptation. Coupled with a sliding window scheme for better performance and an averaging method for noise reduction, the improved algorithm can efficiently construct open‐loop controls for long and challenging reference motions in good quality. Our ideas are intuitive and the implementations are simple. We compare the improved algorithm with the original algorithm both qualitatively and quantitatively, and demonstrate the effectiveness of the improved algorithm with a variety of motions ranging from stylized walking and dancing to gymnastic and Martial Arts routines.     

Exploratory Visualization of Animal Kinematics Using Instantaneous Helical Axes

We present novel visual and interactive techniques for exploratory visualization of animal kinematics using instantaneous helical axes (IHAs). The helical axis has been used in orthopedics, biomechanics, and structural mechanics as a construct for describing rigid body motion. Within biomechanics, recent imaging advances have made possible accurate high‐speed measurements of individual bone positions and orientations during experiments. From this high‐speed data, instantaneous helical axes of motion may be calculated. We address questions of effective interactive, exploratory visualization of this high‐speed 3D motion data. A 3D glyph that encodes all parameters of the IHA in visual form is presented. Interactive controls are used to examine the change in the IHA over time and relate the IHA to anatomical features of interest selected by a user. The techniques developed are applied to a stereoscopic, interactive visualization of the mechanics of pig mastication and assessed by a team of evolutionary biologists who found interactive IHA‐based analysis a useful addition to more traditional motion analysis techniques.     

Fast and Efficient Skinning of Animated Meshes

Skinning is a simple yet popular deformation technique combining compact storage with efficient hardware accelerated rendering. While skinned meshes (such as virtual characters) are traditionally created by artists, previous work proposes algorithms to construct skinning automatically from a given vertex animation. However, these methods typically perform well only for a certain class of input sequences and often require long pre‐processing times. We present an algorithm based on iterative coordinate descent optimization which handles arbitrary animations and produces more accurate approximations than previous techniques, while using only standard linear skinning without any modifications or extensions. To overcome the computational complexity associated with the iterative optimization, we work in a suitable linear subspace (obtained by quick approximate dimensionality reduction) and take advantage of the typically very sparse vertex weights. As a result, our method requires about one or two orders of magnitude less pre‐processing time than previous methods.     

Creating and Preserving Vortical Details in SPH Fluid

We present a new method to create and preserve the turbulent details generated around moving objects in SPH fluid. In our approach, a high‐resolution overlapping grid is bounded to each object and translates with the object. The turbulence formation is modeled by resolving the local flow around objects using a hybrid SPH‐FLIP method. Then these vortical details are carried on SPH particles flowing through the local region and preserved in the global field in a synthetic way. Our method provides a physically plausible way to model the turbulent details around both rigid and deformable objects in SPH fluid, and can efficiently produce animations of complex gaseous phenomena with rich visual details.     

Animated 3D Line Drawings with Temporal Coherence

Producing traditional animation is a laborious task where the key drawings are first drawn by artists and thereafter inbetween drawings are created, whether it is by hand or computer‐assisted. Auto‐inbetweening of these 2D key drawings by computer is a non‐trivial task as 3D depths are missing. An alternate approach is to generate all the drawings by extracting lines directly from animated 3D models frame by frame, concatenating and rendering them together into an animation. However, animation quality generated using this straightforward method bears two problems. Firstly, the animation contains unsatisfactory visual artifacts such as line flickering and popping. This is especially pronounced when the lines are extracted using high‐order derivatives, such as ridges and valleys, from 3D models represented in triangle meshes. Secondly, there is a lack of temporal continuity as each drawing is generated without taking its neighboring drawings into consideration. In this paper, we propose an improved approach over the straightforward method by transferring extracted 3D line drawings of each frame into individual 3D lines and processing them along the time domain. Our objective is to minimize the visual artifacts and incorporate temporal relationship of individual lines throughout the entire animation sequence. This is achieved by creating correspondent trajectory of each line from each frame and applying global optimization on each trajectory. To realize this target, we present a fully automatic novel approach, which consists of (1) a line matching algorithm, (2) an optimizing algorithm, taking into account both the variations of numbers and lengths of 3D lines in each frame, and (3) a robust tracing method for transferring collections of line segments extracted from the 3D models into individual lines. We evaluate our approach on several animated model sequences to demonstrate its effectiveness in producing line drawing animations with temporal coherence.     

Procedural Synthesis using Vortex Particle Method for Fluid Simulation

We propose a fast and effective technique to improve sub‐grid visual details of the grid based fluid simulation. Our method procedurally synthesizes the flow fields coming from the incompressible Navier‐Stokes solver and the vorticity fields generated by vortex particle method for sub‐grid turbulence. We are able to efficiently animate smoke which is highly turbulent and swirling with small scale details. Since this technique does not solve the linear system in high‐resolution grids, it can perform fluid simulation more rapidly. We can easily estimate the influence of turbulent and swirling effect to the fluid flow.     

Manifold‐Based 3D Face Caricature Generation with Individualized Facial Feature Extraction

Caricature is an interesting art to express exaggerated views of different persons and things through drawing. The face caricature is popular and widely used for different applications. To do this, we have to properly extract unique/specialized features of a person's face. A person's facial feature not only depends on his/her natural appearance, but also the associated expression style. Therefore, we would like to extract the neutural facial features and personal expression style for different applicaions. In this paper, we represent the 3D neutral face models in BU–3DFE database by sparse signal decomposition in the training phase. With this decomposition, the sparse training data can be used for robust linear subspace modeling of public faces. For an input 3D face model, we fit the model and decompose the 3D model geometry into a neutral face and the expression deformation separately. The neutral geomertry can be further decomposed into public face and individualized facial feature. We exaggerate the facial features and the expressions by estimating the probability on the corresponding manifold. The public face, the exaggerated facial features and the exaggerated expression are combined to synthesize a 3D caricature for a 3D face model. The proposed algorithm is automatic and can effectively extract the individualized facial features from an input 3D face model to create 3D face caricature.