Adaptive Volumetric Shadow Maps

We introduce adaptive volumetric shadow maps (AVSM), a real‐time shadow algorithm that supports high‐quality shadowing from dynamic volumetric media such as hair and smoke. The key contribution of AVSM is the introduction of a streaming simplification algorithm that generates an accurate volumetric light attenuation function using a small fixed memory footprint. This compression strategy leads to high performance because the visibility data can remain in on‐chip memory during simplification and can be efficiently sampled during rendering. We demonstrate that AVSM compression closely approximates the ground‐truth correct solution and performs competitively to existing real‐time rendering techniques while providing higher quality volumetric shadows.     

Multi‐View Stereo on Consistent Face Topology

We present a multi‐view stereo reconstruction technique that directly produces a complete high‐fidelity head model with consistent facial mesh topology. While existing techniques decouple shape estimation and facial tracking, our framework jointly optimizes for stereo constraints and consistent mesh parameterization. Our method is therefore free from drift and fully parallelizable for dynamic facial performance capture. We produce highly detailed facial geometries with artist‐quality UV parameterization, including secondary elements such as eyeballs, mouth pockets, nostrils, and the back of the head. Our approach consists of deforming a common template model to match multi‐view input images of the subject, while satisfying cross‐view, cross‐subject, and cross‐pose consistencies using a combination of 2D landmark detection, optical flow, and surface and volumetric Laplacian regularization. Since the flow is never computed between frames, our method is trivially parallelized by processing each frame independently. Accurate rigid head pose is extracted using a PCA‐based dimension reduction and denoising scheme. We demonstrate high‐fidelity performance capture results with challenging head motion and complex facial expressions around eye and mouth regions. While the quality of our results is on par with the current state‐of‐the‐art, our approach can be fully parallelized, does not suffer from drift, and produces face models with production‐quality mesh topologies.     

Real‐Time Temporal‐Coherent Color Contrast Enhancement for Dichromats

We present an automatic image‐recoloring technique for enhancing color contrast for dichromats whose computational cost varies linearly with the number of input pixels. Our approach can be efficiently implemented on GPUs, and we show that for typical image sizes it is up to two orders of magnitude faster than the current state‐of‐the‐art technique. Unlike previous approaches, ours preserve temporal coherence and, therefore, is suitable for video recoloring. We demonstrate the effectiveness of our technique by integrating it into a visualization system and showing, for the first time, real‐time high‐quality recolored visualizations for dichromats.     

Adaptive Cross‐sections of Anatomical Models

Medical illustrations have been used for a long time for teaching and communicating information for diagnosis or surgery planning. Illustrative visualization systems create methods and tools that adapt traditional illustration techniques to enhance the result of renderings. Clipping the volume is a popular operation in volume rendering for inspecting the inner parts, though it may remove some information of the context that is worth preserving. In this paper we present a new editing technique based on the use of clipping planes, direct structure extrusion, and illustrative methods, which preserves the context by adapting the extruded region to the structures of interest of the volumetric model. We will show that users may interactively modify the clipping plane and edit the structures to highlight, in order to easily create the desired result. Our approach works with segmented volume models and non‐segmented ones. In the last case, a local segmentation is performed on‐the‐fly. We will demonstrate the efficiency and utility of our method.     

Topology Aware Data‐Driven Inverse Kinematics

Creating realistic human movement is a time consuming and labour intensive task. The major difficulty is that the user has to edit individual joints while maintaining an overall realistic and collision free posture. Previous research suggests the use of data‐driven inverse kinematics, such that one can focus on the control of a few joints, while the system automatically composes a natural posture. However, as a common problem of kinematics synthesis, penetration of body parts is difficult to avoid in complex movements. In this paper, we propose a new data‐driven inverse kinematics framework that conserves the topology of the synthesizing postures. Our system monitors and regulates the topology changes using the Gauss Linking Integral (GUI), such that penetration can be efficiently prevented. As a result, complex motions with tight body movements, as well as those involving interaction with external objects, can be simulated with minimal manual intervention. Experimental results show that using our system, the user can create high quality human motion in real‐time by controlling a few joints using a mouse or a multi‐touch screen. The movement generated is both realistic and penetration free. Our system is best applied for interactive motion design in computer animations and games.     

Live Video Montage with a Rotating Camera

High‐quality video editing usually requires accurate layer separation in order to resolve occlusions. However, most of the existing bilayer segmentation algorithms require either considerable user intervention or a simple stationary camera configuration with known background, which is difficult to meet for many real world online applications. This paper demonstrates that various visually appealing montage effects can be online created from a live video captured by a rotating camera, by accurately retrieving the camera state and segmenting out the dynamic foreground. The key contribution is that a novel fast bilayer segmentation method is proposed which can effectively extract the dynamic foreground under rotational camera configuration, and is robust to imperfect background estimation and complex background colors. Our system can create a variety of live visual effects, including but not limited to, realistic virtual object insertion, background substitution and blurring, non‐photorealistic rendering and camouflage effect. A variety of challenging examples demonstrate the effectiveness of our method.     

Efficient Volumetric PolyCube‐Map Construction

PolyCubes provide compact representations for closed complex shapes and are essential to many computer graphics applications. Existing automatic PolyCube construction methods usually suffer from poor quality or time‐consuming computation. In this paper, we provide a highly efficient method to compute volumetric PolyCube‐maps. Given an input tetrahedral mesh, we utilize two novel normal‐driven volumetric deformation schemes and a polycube‐allowable mesh segmentation to drive the input to a volumetric PolyCube structure. Our method can robustly generate foldover‐free and low‐distortion PolyCube‐maps in practice, and provide a flexible control on the number of corners of Polycubes. Compared with state‐of‐the‐art methods, our method is at least one order of magnitude faster and has better mapping qualities. We demonstrate the efficiency and efficacy of our method in PolyCube construction and all‐hexahedral meshing on various complex models.     

Guided Volume Editing based on Histogram Dissimilarity

Segmentation of volumetric data is an important part of many analysis pipelines, but frequently requires manual inspection and correction. While plenty of volume editing techniques exist, it remains cumbersome and errorprone for the user to find and select appropriate regions for editing. We propose an approach to improve volume editing by detecting potential segmentation defects while considering the underlying structure of the object of interest. Our method is based on a novel histogram dissimilarity measure between individual regions, derived from structural information extracted from the initial segmentation. Based on this information, our interactive system guides the user towards potential defects, provides integrated tools for their inspection, and automatically generates suggestions for their resolution. We demonstrate that our approach can reduce interaction effort and supports the user in a comprehensive investigation for high‐quality segmentations.     

Shape Matching via Quotient Spaces

We introduce a novel method for non‐rigid shape matching, designed to address the symmetric ambiguity problem present when matching shapes with intrinsic symmetries. Unlike the majority of existing methods which try to overcome this ambiguity by sampling a set of landmark correspondences, we address this problem directly by performing shape matching in an appropriate quotient space, where the symmetry has been identified and factored out. This allows us to both simplify the shape matching problem by matching between subspaces, and to return multiple solutions with equally good dense correspondences. Remarkably, both symmetry detection and shape matching are done without establishing any landmark correspondences between either points or parts of the shapes. This allows us to avoid an expensive combinatorial search present in most intrinsic symmetry detection and shape matching methods. We compare our technique with state‐of‐the‐art methods and show that superior performance can be achieved both when the symmetry on each shape is known and when it needs to be estimated.     

Hybrid Data Visualization Based on Depth Complexity Histogram Analysis

In many cases, only the combination of geometric and volumetric data sets is able to describe a single phenomenon under observation when visualizing large and complex data. When semi‐transparent geometry is present, correct rendering results require sorting of transparent structures. Additional complexity is introduced as the contributions from volumetric data have to be partitioned according to the geometric objects in the scene. The A‐buffer, an enhanced framebuffer with additional per‐pixel information, has previously been introduced to deal with the complexity caused by transparent objects. In this paper, we present an optimized rendering algorithm for hybrid volume‐geometry data based on the A‐buffer concept. We propose two novel components for modern GPUs that tailor memory utilization to the depth complexity of individual pixels. The proposed components are compatible with modern A‐buffer implementations and yield performance gains of up to eight times compared to existing approaches through reduced allocation and reuse of fast cache memory. We demonstrate the applicability of our approach and its performance with several examples from molecular biology, space weather and medical visualization containing both, volumetric data and geometric structures.     

Modeling Complex Unfoliaged Trees from a Sparse Set of Images

We present a novel image‐based technique for modeling complex unfoliaged trees. Existing tree modeling tools either require capturing a large number of views for dense 3D reconstruction or rely on user inputs and botanic rules to synthesize natural‐looking tree geometry. In this paper, we focus on faithfully recovering real instead of realistically‐looking tree geometry from a sparse set of images. Our solution directly integrates 2D/3D tree topology as shape priors into the modeling process. For each input view, we first estimate a 2D skeleton graph from its matte image and then find a 2D skeleton tree from the graph by imposing tree topology. We develop a simple but effective technique for computing the optimal 3D skeleton tree most consistent with the 2D skeletons. For each edge in the 3D skeleton tree, we further apply volumetric reconstruction to recover its corresponding curved branch. Finally, we use piecewise cylinders to approximate each branch from the volumetric results. We demonstrate our framework on a variety of trees to illustrate the robustness and usefulness of our technique.     

Matting and Compositing for Fresnel Reflection on Wavy Surfaces

This paper introduces a framework that can extract an alpha matte from a single image with Fresnel reflection, and that can composite other objects with the image such that plausible reflections are included. Our method handles reflections in a plane with small undulations, for example, a water surface with waves or a glossy tabletop. During the matting stage, our method first estimates the transmission color, which is assumed to be uniform, and then calculates a reflection image and alpha matte based on user markups. However, accurate extraction of the matte becomes challenging when a plane has small undulations because these create perturbations in the matte. We therefore propose a filter that can refine the matte effectively. In the compositing stage, the reflection of a composited object is synthesized by ray tracing in real time. We demonstrate the effectiveness of our method through comparisons with ground‐truth data and results using natural images as inputs.     

Shared Sampling for Real‐Time Alpha Matting

Image matting aims at extracting foreground elements from an image by means of color and opacity (alpha) estimation. While a lot of progress has been made in recent years on improving the accuracy of matting techniques, one common problem persisted: the low speed of matte computation. We present the first real‐time matting technique for natural images and videos. Our technique is based on the observation that, for small neighborhoods, pixels tend to share similar attributes. Therefore, independently treating each pixel in the unknown regions of a trimap results in a lot of redundant work. We show how this computation can be significantly and safely reduced by means of a careful selection of pairs of background and foreground samples. Our technique achieves speedups of up to two orders of magnitude compared to previous ones, while producing high‐quality alpha mattes. The quality of our results has been verified through an independent benchmark. The speed of our technique enables, for the first time, real‐time alpha matting of videos, and has the potential to enable a new class of exciting applications.     

Raycasting of Light Field Galleries from Volumetric Data

The paper describes a technique to generate high‐quality light field representations from volumetric data. We show how light field galleries can be created to give unexperienced audiences access to interactive high‐quality volume renditions. The proposed light field representation is lightweight with respect to storage and bandwidth capacity and is thus ideal as exchange format for visualization results, especially for web galleries. The approach expands an existing sphere‐hemisphere parameterization for the light field with per‐pixel depth. High‐quality paraboloid maps from volumetric data are generated using GPU‐based ray‐casting or slicing approaches. Different layers, such as isosurfaces, but not restricted to, can be generated independently and composited in real time. This allows the user to interactively explore the model and to change visibility parameters at run‐time.     

Level‐of‐Detail Streaming and Rendering using Bidirectional Sparse Virtual Texture Functions

Bidirectional Texture Functions (BTFs) are among the highest quality material representations available today and thus well suited whenever an exact reproduction of the appearance of a material or complete object is required. In recent years, BTFs have started to find application in various industrial settings and there is also a growing interest in the cultural heritage domain. BTFs are usually measured from real‐world samples and easily consist of tens or hundreds of gigabytes. By using data‐driven compression schemes, such as matrix or tensor factorization, a more compact but still faithful representation can be derived. This way, BTFs can be employed for real‐time rendering of photo‐realistic materials on the GPU. However, scenes containing multiple BTFs or even single objects with high‐resolution BTFs easily exceed available GPU memory on today's consumer graphics cards unless quality is drastically reduced by the compression. In this paper, we propose the Bidirectional Sparse Virtual Texture Function, a hierarchical level‐of‐detail approach for the real‐time rendering of large BTFs that requires only a small amount of GPU memory. More importantly, for larger numbers or higher resolutions, the GPU and CPU memory demand grows only marginally and the GPU workload remains constant. For this, we extend the concept of sparse virtual textures by choosing an appropriate prioritization, finding a trade off between factorization components and spatial resolution. Besides GPU memory, the high demand on bandwidth poses a serious limitation for the deployment of conventional BTFs. We show that our proposed representation can be combined with an additional transmission compression and then be employed for streaming the BTF data to the GPU from from local storage media or over the Internet. In combination with the introduced prioritization this allows for the fast visualization of relevant content in the users field of view and a consecutive progressive refinement.     

Approximate on‐Surface Distance Computation using Quasi‐Developable Charts

There is a vast number of applications that require distance field computation over triangular meshes. State‐of‐the‐art algorithms have quadratic or sub‐quadratic worst‐case complexity, making them impractical for interactive applications. While most of the research on this subject has been focused on reducing the computation complexity of the algorithms, in this work we propose an approximate algorithm that achieves similar results working in lower resolutions of the input meshes. The creation of lower resolution meshes is the essence of our proposal. The idea is to identify regions on the input mesh that can be unfolded into planar regions with minimal area distortion (i.e. quasi‐developable charts). Once charts are computed, their interior is re‐triangulated to reduce the number of triangles, which results in a collection of simplified charts that we call a base mesh. Due to the properties of quasi‐developable regions, we are able to compute distance fields over the base mesh instead of over the input mesh. This reduces the memory footprint and data processed for distance computations, which is the bottleneck of these algorithms. We present results that are one order of magnitude faster than current exact solutions, with low approximation errors.     

Interactive High‐Quality Visualization of Higher‐Order Finite Elements

Higher‐order finite element methods have emerged as an important discretization scheme for simulation. They are increasingly used in contemporary numerical solvers, generating a new class of data that must be analyzed by scientists and engineers. Currently available visualization tools for this type of data are either batch oriented or limited to certain cell types and polynomial degrees. Other approaches approximate higher‐order data by resampling resulting in trade‐offs in interactivity and quality. To overcome these limitations, we have developed a distributed visualization system which allows for interactive exploration of non‐conforming unstructured grids, resulting from space‐time discontinuous Galerkin simulations, in which each cell has its own higher‐order polynomial solution. Our system employs GPU‐based raycasting for direct volume rendering of complex grids which feature non‐convex, curvilinear cells with varying polynomial degree. Frequency‐based adaptive sampling accounts for the high variations along rays. For distribution across a GPU cluster, the initial object‐space partitioning is determined by cell characteristics like the polynomial degree and is adapted at runtime by a load balancing mechanism. The performance and utility of our system is evaluated for different aeroacoustic simulations involving the propagation of shock fronts.     

BetweenIT: An Interactive Tool for Tight Inbetweening

The generation of inbetween frames that interpolate a given set of key frames is a major component in the production of a 2D feature animation. Our objective is to considerably reduce the cost of the inbetweening phase by offering an intuitive and effective interactive environment that automates inbetweening when possible while allowing the artist to guide, complement, or override the results. Tight inbetweens, which interpolate similar key frames, are particularly time‐consuming and tedious to draw. Therefore, we focus on automating these high‐precision and expensive portions of the process. We have designed a set of user‐guided semi‐automatic techniques that fit well with current practice and minimize the number of required artist‐gestures. We present a novel technique for stroke interpolation from only two keys which combines a stroke motion constructed from logarithmic spiral vertex trajectories with a stroke deformation based on curvature averaging and twisting warps. We discuss our system in the context of a feature animation production environment and evaluate our approach with real production data.     

An Example‐based Approach to Synthesize Artistic Strokes using Graphs

In this paper, we propose a technique to produce artistic strokes in a variety of drawing material based on example images. Our approach is to divide example strokes scanned from images into small pieces along their stroke directions and synthesize a novel stroke by rearranging them along a user specified curve. The visible quality of a synthesized stroke can be maintained by utilizing the connectivity information stored in a directed graph constructed in the preprocessing step. At run‐time, the graph is traversed to find a path best matching the user specification given as a curve and additional information. The results of our experiments shows that visually convincing strokes of various materials can be generated efficiently.     

L4RW: Laziness‐based Realistic Real‐time Responsive Rebalance in Walking

We present a novel L4RW (Laziness‐based Realistic Real‐time Responsive Rebalance in Walking) technique to synthesize 4RW animations under unexpected external perturbations with minimal locomotion effort. We first devise a lazy dynamic rebalance model, which specifies the dynamic balance conditions, defines the rebalance effort, and selects the suitable rebalance strategy automatically using the laziness law after an unexpected perturbation. Based on the model, L4RW searches over a motion capture (mocap) database for an appropriate motion segment to follow, and the transition‐to motions is generated by interpolating the active response dynamic motion. A support vector machine (SVM) based training, classification, and predication algorithm is applied to reduce the search space, and it is trained offline only once. Our algorithm classifies the mocap database into many rebalance strategy‐specified subsets and then online predicts responsive motions in the subset according to the selected strategy. The rebalance effort, the ‘extrapolated center of mass’ (XCoM) and environment constraints are selected as feature attributes for the SVM feature vector. Furthermore, the subset's segments are sorted through the rebalance effort, then our algorithm searches for an acceptable segment starting from the least‐effort segment. Compared with previous methods, our search increases speed by over two orders of magnitude, and our algorithm creates more realistic and smooth 4RW animation.