Modal Locomotion: Animating Virtual Characters with Natural Vibrations

We present a general method to intuitively create a wide range of locomotion controllers for 3D legged characters. The key of our approach is the assumption that efficient locomotion can exploit the natural vibration modes of the body, where these modes are related to morphological parameters such as the shape, size, mass, and joint stiffness. The vibration modes are computed for a mechanical model of any 3D character with rigid bones, elastic joints, and additional constraints as desired. A small number of vibration modes can be selected with respect to their relevance to locomotion patterns and combined into a compact controller driven by very few parameters. We show that these controllers can be used in dynamic simulations of simple creatures, and for kinematic animations of more complex creatures of a variety of shapes and sizes.     

Online Motion Capture Marker Labeling for Multiple Interacting Articulated Targets

In this paper, we propose an online motion capture marker labeling approach for multiple interacting articulated targets. Given hundreds of unlabeled motion capture markers from multiple articulated targets that are interacting each other, our approach automatically labels these markers frame by frame, by fitting rigid bodies and exploiting trained structure and motion models. Advantages of our approach include: 1) our method is an online algorithm, which requires no user interaction once the algorithm starts. 2) Our method is more robust than traditional the closest point-based approaches by automatically imposing the structure and motion models. 3) Due to the use of the structure model which encodes the rigidity of each articulated body of captured targets, our method can recover missing markers robustly. Our approach is efficient and particularly suited for online computer animation and video game applications.     

Character Motion Synthesis by Topology Coordinates

In this paper, we propose a new method to efficiently synthesize character motions that involve close contacts such as wearing a T-shirt, passing the arms through the strings of a knapsack, or piggy-back carrying an injured person. We introduce the concept of topology coordinates, in which the topological relationships of the segments are embedded into the attributes. As a result, the computation for collision avoidance can be greatly reduced for complex motions that require tangling the segments of the body. Our method can be combinedly used with other prevalent frame-based optimization techniques such as inverse kinematics.     

An Adaptive Contact Model for the Robust Simulation of Knots

In this paper, we present an adaptive model for dynamically deforming hyper‐elastic rods. In contrast to existing approaches, adaptively introduced control points are not governed by geometric subdivision rules. Instead, their states are determined by employing a non‐linear energy‐minimization approach. Since valid control points are computed instantaneously, post‐stabilization schemes are avoided and the stability of the dynamic simulation is improved. Due to inherently complex contact configurations, the simulation of knot tying using rods is a challenging task. In order to address this problem, we combine our adaptive model with a robust and accurate collision handling method for elastic rods. By employing our scheme, complex knot configurations can be simulated in a physically plausible way.     

Mixing Fluids and Granular Materials

Fluid animations in computer graphics show interactions with various kinds of objects. However, fluid flowing through a granular material such as sand is still not possible within current frameworks. In this paper, we present the simulation of fine granular materials interacting with fluids. We propose a unified Smoothed Particle Hydrodynamics framework for the simulation of both fluid and granular material. The granular volume is simulated as a continuous material sampled by particles. By incorporating previous work on porous flow in this simulation framework we are able to fully couple fluid and sand. Fluid can now percolate between sand grains and influence the physical properties of the sand volume. Our method demonstrates various new effects such as dry soil transforming into mud pools by rain or rigid sand structures being eroded by waves.     

Single Photo Estimation of Hair Appearance

Significant progress has been made in high-quality hair rendering, but it remains difficult to choose parameter values that reproduce a given real hair appearance. In particular, for applications such as games where naive users want to create their own avatars, tuning complex parameters is not practical. Our approach analyses a single flash photograph and estimates model parameters that reproduce the visual likeness of the observed hair. The estimated parameters include color absorptions, three reflectance lobe parameters of a multiple-scattering rendering model, and a geometric noise parameter. We use a novel melanin-based model to capture the natural subspace of hair absorption parameters. At its core, the method assumes that images of hair with similar color distributions are also similar in appearance. This allows us to recast the issue as an image retrieval problem where the photo is matched with a dataset of rendered images; we thus also match the model parameters used to generate these images. An earth-mover's distance is used between luminance-weighted color distributions to gauge similarity. We conduct a perceptual experiment to evaluate this metric in the context of hair appearance and demonstrate the method on 64 photographs, showing that it can achieve a visual likeness for a large variety of input photos.     

Hierarchical Image-Space Radiosity for Interactive Global Illumination

We introduce image-space radiosity and a hierarchical variant as a method for interactively approximating diffuse indirect illumination in fully dynamic scenes. As oft observed, diffuse indirect illumination contains mainly low-frequency details that do not require independent computations at every pixel. Prior work leverages this to reduce computation costs by clustering and caching samples in world or object space. This often involves scene preprocessing, complex data structures for caching, or wasted computations outside the view frustum. We instead propose clustering computations in image space, allowing the use of cheap hardware mipmapping and implicit quadtrees to allow coarser illumination computations. We build on a recently introduced multiresolution splatting technique combined with an image-space lightcut algorithm to intelligently choose virtual point lights for an interactive, one-bounce instant radiosity solution. Intelligently selecting point lights from our reflective shadow map enables temporally coherent illumination similar to results using more than 4096 regularly-sampled VPLs.     

Efficient and Accurate Rendering of Complex Light Sources

We present a new method for estimating the radiance function of complex area light sources. The method is based on Jensen's photon mapping algorithm. In order to capture high angular frequencies in the radiance function, we incorporate the angular domain into the density estimation. However, density estimation in position-direction space makes it necessary to find a tradeoff between the spatial and angular accuracy of the estimation. We identify the parameters which are important for this tradeoff and investigate the typical estimation errors. We show how the large data size, which is inherent to the underlying problem, can be handled. The method is applied to different automotive tail lights. It can be applied to a wide range of other real-world light sources.     

Estimating Specular Roughness and Anisotropy from Second Order Spherical Gradient Illumination

This paper presents a novel method for estimating specular roughness and tangent vectors, per surface point, from polarized second order spherical gradient illumination patterns. We demonstrate that for isotropic BRDFs, only three second order spherical gradients are sufficient to robustly estimate spatially varying specular roughness. For anisotropic BRDFs, an additional two measurements yield specular roughness and tangent vectors per surface point. We verify our approach with different illumination configurations which project both discrete and continuous fields of gradient illumination. Our technique provides a direct estimate of the per-pixel specular roughness and thus does not require off-line numerical optimization that is typical for the measure-and-fit approach to classical BRDF modeling.     

Adaptive Caustic Maps Using Deferred Shading

Caustic maps provide an interactive image-space method to render caustics, the focusing of light via reflection and refraction. Unfortunately, caustic mapping suffers problems similar to shadow mapping: aliasing from poor sampling and map projection as well as temporal incoherency from frame-to-frame sampling variations. To reduce these problems, researchers have suggested methods ranging from caustic blurring to building a multiresolution caustic map. Yet these all require a fixed photon sampling, precluding the use of importance-based photon densities. This paper introduces adaptive caustic maps. Instead of densely sampling photons via a rasterization pass, we adaptively emit photons using a deferred shading pass. We describe deferred rendering for refractive surfaces, which speeds rendering of refractive geometry up to 25% and with adaptive sampling speeds caustic rendering up to 200%. These benefits are particularly noticable for complex geometry or using millions of photons. While developed for a GPU rasterizer, adaptive caustic map creation can be performed by any renderer that individually traces photons, e.g., a GPU ray tracer.     

Enclosing Surfaces for Point Clusters Using 3D Discrete Voronoi Diagrams

Point clusters occur in both spatial and non-spatial data. In the former context they may represent segmented particle data, in the latter context they may represent clusters in scatterplots. In order to visualize such point clusters, enclosing surfaces lead to much better comprehension than pure point renderings.
We propose a flexible system for the generation of enclosing surfaces for 3D point clusters. We developed a GPU-based 3D discrete Voronoi diagram computation that supports all surface extractions. Our system provides three different types of enclosing surfaces. By generating a discrete distance field to the point cluster and extracting an isosurface from the field, an enclosing surface with any distance to the point cluster can be generated. As a second type of enclosing surfaces, a hull of the point cluster is extracted. The generation of the hull uses a projection of the discrete Voronoi diagram of the point cluster to an isosurface to generate a polygonal surface. Generated hulls of non-convex clusters are also non-convex. The third type of enclosing surfaces can be created by computing a distance field to the hull and extracting an isosurface from the distance field. This method exhibits reduced bumpiness and can extract surfaces arbitrarily close to the point cluster without losing connectedness.
We apply our methods to the visualization of multidimensional spatial and non-spatial data. Multidimensional clusters are extracted and projected into a 3D visual space, where the point clusters are visualized. The respective clusters can also be visualized in object space when dealing with multidimensional particle data.     

Expressive Facial Gestures From Motion Capture Data

Human facial gestures often exhibit such natural stochastic variations as how often the eyes blink, how often the eyebrows and the nose twitch, and how the head moves while speaking. The stochastic movements of facial features are key ingredients for generating convincing facial expressions. Although such small variations have been simulated using noise functions in many graphics applications, modulating noise functions to match natural variations induced from the affective states and the personality of characters is difficult and not intuitive. We present a technique for generating subtle expressive facial gestures (facial expressions and head motion) semi‐automatically from motion capture data. Our approach is based on Markov random fields that are simulated in two levels. In the lower level, the coordinated movements of facial features are captured, parameterized, and transferred to synthetic faces using basis shapes. The upper level represents independent stochastic behavior of facial features. The experimental results show that our system generates expressive facial gestures synchronized with input speech.     

Effect of Character Animacy and Preparatory Motion on Perceptual Magnitude of Errors in Ballistic Motion

An increasing number of projects have examined the perceptual magnitude of visible artifacts in animated motion. These studies have been performed using a mix of character types, from detailed human models to abstract geometric objects such as spheres. We explore the extent to which character morphology influences user sensitivity to errors in a fixed set of ballistic motions replicated on three different character types. We find user sensitivity responds to changes in error type or magnitude in a similar manner regardless of character type, but that users display a higher sensitivity to some types of errors when these errors are displayed on more human‐like characters. Further investigation of those error types suggests that being able to observe a period of preparatory motion before the onset of ballistic motion may be important. However, we found no evidence to suggest that a mismatch between the preparatory phase and the resulting ballistic motion was responsible for the higher sensitivity to errors that was observed for the most humanlike character.     

Visualizing Underwater Ocean Optics

Simulating the in‐water ocean light field is a daunting task. Ocean waters are one of the richest participating media, where light interacts not only with water molecules, but with suspended particles and organic matter as well. The concentration of each constituent greatly affects these interactions, resulting in very different hues. Inelastic scattering events such as fluorescence or Raman scattering imply energy transfers that are usually neglected in the simulations. Our contributions in this paper are a bio‐optical model of ocean waters suitable for computer graphics simulations, along with an improved method to obtain an accurate solution of the in‐water light field based on radiative transfer theory. The method provides a link between the inherent optical properties that define the medium and its apparent optical properties, which describe how it looks. The bio‐optical model of the ocean uses published data from oceanography studies. For inelastic scattering we compute all frequency changes at higher and lower energy values, based on the spectral quantum efficiency function of the medium. The results shown prove the usability of the system as a predictive rendering algorithm. Areas of application for this research span from underwater imagery to remote sensing; the resolution method is general enough to be usable in any type of participating medium simulation.     

A Semi-Lagrangian CIP Fluid Solver without Dimensional Splitting

In this paper, we propose a new constrained interpolation profile (CIP) method that is stable and accurate but requires less amount of computation compared to existing CIP‐based solvers. CIP is a high‐order fluid advection solver that can reproduce rich details of fluids. It has third‐order accuracy but its computation is performed over a compact stencil. These advantageous features of CIP are, however, diluted by the following two shortcomings: (1) CIP contains a defect in the utilization of the grid data, which makes the method suitable only for simulations with a tight CFL restriction; and (2) CIP does not guarantee unconditional stability. There have been several attempts to fix these problems in CIP, but they have been only partially successful. The solutions that fixed both problems ended up introducing other undesirable features, namely increased computation time and/or reduced accuracy. This paper proposes a novel modification of the original CIP method that fixes all of the above problems without increasing the computational load or reducing the accuracy. Both quantitative and visual experiments were performed to test the performance of the new CIP in comparison to existing fluid solvers. The results show that the proposed method brings significant improvements in both accuracy and speed.     

Simulation of two-phase flow with sub-scale droplet and bubble effects

We present a new Eulerian-Lagrangian method for physics-based simulation of fluid flow, which includes automatic generation of sub-scale spray and bubbles. The Marker Level Set method is used to provide a simple geometric criterion for free marker generation. A filtering method, inspired from Weber number thresholding, further controls the free marker generation (in a physics-based manner). Two separate models are used, one for sub-scale droplets, the other for sub-scale bubbles. Droplets are evolved in a Newtonian manner, using a density-extension drag force field, while bubbles are evolved using a model based on Stokes' Law. We show that our model for sub-scale droplet and bubble dynamics is simple to couple with a full (macro-scale) Navier-Stokes two-phase flow model and is quite powerful in its applications. Our animations include coarse grained multiphase features interacting with fine scale multiphase features.     

Spectral-Based Group Formation Control

Given a pair of keyframe formations for a group consisting of multiple individuals, we present a spectral-based approach to smoothly transforming a source group formation into a target formation while respecting the clusters of the involved individuals. The proposed method provides an effective means for controlling the macroscopic spatiotemporal arrangement of individuals for applications such as expressive formations in mass performances and tactical formations in team sports. Our main idea is to formulate this problem as rotation interpolation of the eigenbases for the Laplacian matrices, each of which represents how the individuals are clustered in a given keyframe formation. A stream of time-varying formations is controlled by editing the underlying adjacency relationships among individuals as well as their spatial positions at each keyframe, and interpolating the keyframe formations while producing plausible collective behaviors over a period of time. An interactive system of editing existing group behaviors in a hierarchical fashion has been implemented to provide flexible formation control of large crowds.     

Single-pass Scalable Subsurface Rendering with Lightcuts

This paper presents a new, scalable, single pass algorithm for computing subsurface scattering using the diffusion approximation. Instead of pre‐computing a globally conservative estimate of the surface irradiance like previous two pass methods, the algorithm simultaneously refines hierarchical and adaptive estimates of both the surface irradiance and the subsurface transport. By using an adaptive, top‐down refinement method, the algorithm directs computational effort only to simulating those eye‐surface‐light paths that make significant contributions to the final image. Because the algorithm is driven by image importance, it scales more efficiently than previous methods that have a linear dependence on translucent surface area. We demonstrate that in scenes with many translucent objects and in complex lighting environments, our new algorithm has a significant performance advantage.     

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.