36-Issue 2

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https://diglib.eg.org/handle/10.2312/2631245

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Parallel BVH Construction using Progressive Hierarchical Refinement
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Hendrich, Jakub; Meister, Daniel; Bittner, Jiří; Loic Barthe and Bedrich Benes
We propose a novel algorithm for construction of bounding volume hierarchies (BVHs) for multi-core CPU architectures. The algorithm constructs the BVH by a divisive top-down approach using a progressively refined cut of an existing auxiliary BVH. We propose a new strategy for refining the cut that significantly reduces the workload of individual steps of BVH construction. Additionally, we propose a new method for integrating spatial splits into the BVH construction algorithm. The auxiliary BVH is constructed using a very fast method such as LBVH based on Morton codes. We show that the method provides a very good trade-off between the build time and ray tracing performance. We evaluated the method within the Embree ray tracing framework and show that it compares favorably with the Embree BVH builders regarding build time while maintaining comparable ray tracing speed.
Interactive Paper Tearing
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Schreck, Camille; Rohmer, Damien; Hahmann, Stefanie; Loic Barthe and Bedrich Benes
We propose an efficient method to model paper tearing in the context of interactive modeling. The method uses geometrical information to automatically detect potential starting points of tears. We further introduce a new hybrid geometrical and physical-based method to compute the trajectory of tears while procedurally synthesizing high resolution details of the tearing path using a texture based approach. The results obtained are compared with real paper and with previous studies on the expected geometric paths of paper that tears.
Design Transformations for Rule-based Procedural Modeling
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Lienhard, Stefan; Lau, Cheryl; Müller, Pascal; Wonka, Peter; Pauly, Mark; Loic Barthe and Bedrich Benes
We introduce design transformations for rule-based procedural models, e.g., for buildings and plants. Given two or more procedural designs, each specified by a grammar, a design transformation combines elements of the existing designs to generate new designs. We introduce two technical components to enable design transformations. First, we extend the concept of discrete rule switching to rule merging, leading to a very large shape space for combining procedural models. Second, we propose an algorithm to jointly derive two or more grammars, called grammar co-derivation. We demonstrate two applications of our work: we show that our framework leads to a larger variety of models than previous work, and we show fine-grained transformation sequences between two procedural models.
A Subjective Evaluation of Texture Synthesis Methods
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Kolár, Martin; Debattista, Kurt; Chalmers, Alan; Loic Barthe and Bedrich Benes
This paper presents the results of a user study which quantifies the relative and absolute quality of example-based texture synthesis algorithms. In order to allow such evaluation, a list of texture properties is compiled, and a minimal representative set of textures is selected to cover these. Six texture synthesis methods are compared against each other and a reference on a selection of twelve textures by non-expert participants (N = 67). Results demonstrate certain algorithms successfully solve the problem of texture synthesis for certain textures, but there are no satisfactory results for other types of texture properties. The presented textures and results make it possible for future work to be subjectively compared, thus facilitating the development of future texture synthesis methods.
Hybrid Mesh-volume LoDs for All-scale Pre-filtering of Complex 3D Assets
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Loubet, Guillaume; Neyret, Fabrice; Loic Barthe and Bedrich Benes
We address the problem of constructing appearance-preserving level of details (LoDs) of complex 3D models such as trees. We propose a hybrid method that combines the strengths of mesh and volume representations. Our main idea is to separate macroscopic (i.e. larger than the target spatial resolution) and microscopic (sub-resolution) surfaces at each scale and to treat them differently, because meshes are very efficient at representing macroscopic surfaces while sub-resolution geometry benefits from volumetric approximations. We introduce a new algorithm that detects the macroscopic surfaces of a mesh for a given resolution. We simplify these surfaces with edge collapses and we provide a method for pre-filtering their normal distributions and albedos. To approximate microscopic details, we use a heterogeneous microflake participating medium and we introduce a new artifact-free voxelization algorithm that preserves local occlusion. Thanks to our macroscopic surface analysis, our algorithm is fully automatic and it generates seamless LoDs at arbitrarily coarse resolutions for a wide range of 3D models.
Diffusion Diagrams: Voronoi Cells and Centroids from Diffusion
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Herholz, Philipp; Haase, Felix; Alexa, Marc; Loic Barthe and Bedrich Benes
We define Voronoi cells and centroids based on heat diffusion. These heat cells and heat centroids coincide with the common definitions in Euclidean spaces. On curved surfaces they compare favorably with definitions based on geodesics: they are smooth and can be computed in a stable way with a single linear solve. We analyze the numerics of this approach and can show that diffusion diagrams converge quadratically against the smooth case under mesh refinement, which is better than other common discretization of distance measures in curved spaces. By factorizing the system matrix in a preprocess, computing Voronoi diagrams or centroids amounts to just back-substitution. We show how to localize this operation so that the complexity is linear in the size of the cells and not the underlying mesh. We provide several example applications that show how to benefit from this approach.
Zooming on all Actors: Automatic Focus+Context Split Screen Video Generation
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Kumar, Moneish; Gandhi, Vineet; Ronfard, Rémi; Gleicher, Michael; Loic Barthe and Bedrich Benes
Recordings of stage performances are easy to capture with a high-resolution camera, but are difficult to watch because the actors' faces are too small. We present an approach to automatically create a split screen video that transforms these recordings to show both the context of the scene as well as close-up details of the actors. Given a static recording of a stage performance and tracking information about the actors positions, our system generates videos showing a focus+context view based on computed close-up camera motions using crop-and zoom. The key to our approach is to compute these camera motions such that they are cinematically valid close-ups and to ensure that the set of views of the different actors are properly coordinated and presented. We pose the computation of camera motions as convex optimization that creates detailed views and smooth movements, subject to cinematic constraints such as not cutting faces with the edge of the frame. Additional constraints link the close up views of each actor, causing them to merge seamlessly when actors are close. Generated views are placed in a resulting layout that preserves the spatial relationships between actors. We demonstrate our results on a variety of staged theater and dance performances.
Performance-Based Biped Control using a Consumer Depth Camera
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Lee, Yoonsang; Kwon, Taesoo; Loic Barthe and Bedrich Benes
We present a technique for controlling physically simulated characters using user inputs from an off-the-shelf depth camera. Our controller takes a real-time stream of user poses as input, and simulates a stream of target poses of a biped based on it. The simulated biped mimics the user's actions while moving forward at a modest speed and maintaining balance. The controller is parameterized over a set of modulated reference motions that aims to cover the range of possible user actions. For real-time simulation, the best set of control parameters for the current input pose is chosen from the parameterized sets of pre-computed control parameters via a regression method. By applying the chosen parameters at each moment, the simulated biped can imitate a range of user actions while walking in various interactive scenarios.
Computational Light Painting Using a Virtual Exposure
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Salamon, Nestor Z.; Lancelle, Marcel; Eisemann, Elmar; Loic Barthe and Bedrich Benes
Light painting is an artform where a light source is moved during a long-exposure shot, creating trails resembling a stroke on a canvas. It is very difficult to perform because the light source needs to be moved at the intended speed and along a precise trajectory. Additionally, images can be corrupted by the person moving the light. We propose computational light painting, which avoids such artifacts and is easy to use. Taking a video of the moving light as input, a virtual exposure allows us to draw the intended light positions in a post-process. We support animation, as well as 3D light sculpting, with high-quality results.
Analysis and Controlled Synthesis of Inhomogeneous Textures
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Zhou, Yang; Shi, Huajie; Lischinski, Dani; Gong, Minglun; Kopf, Johannes; Huang, Hui; Loic Barthe and Bedrich Benes
Many interesting real-world textures are inhomogeneous and/or anisotropic. An inhomogeneous texture is one where various visual properties exhibit significant changes across the texture's spatial domain. Examples include perceptible changes in surface color, lighting, local texture pattern and/or its apparent scale, and weathering effects, which may vary abruptly, or in a continuous fashion. An anisotropic texture is one where the local patterns exhibit a preferred orientation, which also may vary across the spatial domain. While many example-based texture synthesis methods can be highly effective when synthesizing uniform (stationary) isotropic textures, synthesizing highly non-uniform textures, or ones with spatially varying orientation, is a considerably more challenging task, which so far has remained underexplored. In this paper, we propose a new method for automatic analysis and controlled synthesis of such textures. Given an input texture exemplar, our method generates a source guidance map comprising: (i) a scalar progression channel that attempts to capture the low frequency spatial changes in color, lighting, and local pattern combined, and (ii) a direction field that captures the local dominant orientation of the texture. Having augmented the texture exemplar with this guidance map, users can exercise better control over the synthesized result by providing easily specified target guidance maps, which are used to constrain the synthesis process.
Sparse Rig Parameter Optimization for Character Animation
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Song, Jaewon; Ribera, Roger Blanco i; Cho, Kyungmin; You, Mi; Lewis, J. P.; Choi, Byungkuk; Noh, Junyong; Loic Barthe and Bedrich Benes
We propose a novel motion retargeting method that efficiently estimates artist-friendly rig space parameters. Inspired by the workflow typically observed in keyframe animation, our approach transfers a source motion into a production friendly character rig by optimizing the rig space parameters while balancing the considerations of fidelity to the source motion and the ease of subsequent editing. We propose the use of an intermediate object to transfer both the skeletal motion and the mesh deformation. The target rig-space parameters are then optimized to minimize the error between the motion of an intermediate object and the target character. The optimization uses a set of artist defined weights to modulate the effect of the different rig space parameters over time. Sparsity inducing regularizers and keyframe extraction streamline any additional editing processes. The results obtained with different types of character rigs demonstrate the versatility of our method and its effectiveness in simplifying any necessary manual editing within the production pipeline.
Unbiased Light Transport Estimators for Inhomogeneous Participating Media
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Szirmay-Kalos, László; Georgiev, Iliyan; Magdics, Milán; Molnár, Balázs; Légrády, Dávid; Loic Barthe and Bedrich Benes
This paper presents a new stochastic particle model for efficient and unbiased Monte Carlo rendering of heterogeneous participating media. We randomly add and remove material particles to obtain a density with which free flight sampling and transmittance estimation are simple, while material particle properties are simultaneously modified to maintain the true expectation of the radiance. We show that meeting this requirement may need the introduction of light particles with negative energy and materials with negative extinction, and provide an intuitive interpretation for such phenomena. Unlike previous unbiased methods, the proposed approach does not require a-priori knowledge of the maximum medium density that is typically difficult to obtain for procedural models. However, the method can benefit from an approximate knowledge of the density, which can usually be acquired on-the-fly at little extra cost and can greatly reduce the variance of the proposed estimators. The introduced mechanism can be integrated in participating media renderers where transmittance estimation and free flight sampling are building blocks. We demonstrate its application in a multiple scattering particle tracer, in transmittance computation, and in the estimation of the inhomogeneous air-light integral.
Informative Descriptor Preservation via Commutativity for Shape Matching
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Nogneng, Dorian; Ovsjanikov, Maks; Loic Barthe and Bedrich Benes
We consider the problem of non-rigid shape matching, and specifically the functional maps framework that was recently proposed to find correspondences between shapes. A key step in this framework is to formulate descriptor preservation constraints that help to encode the information (e.g., geometric or appearance) that must be preserved by the unknown map. In this paper, we show that considering descriptors as linear operators acting on functions through multiplication, rather than as simple scalar-valued signals, allows to extract significantly more information from a given descriptor and ultimately results in a more accurate functional map estimation. Namely, we show that descriptor preservation constraints can be formulated via commutativity with respect to the unknown map, which can be conveniently encoded by considering relations between matrices in the discrete setting. As a result, when the vector space spanned by the descriptors has a dimension smaller than that of the reduced basis, our optimization may still provide a fully-constrained system leading to accurate point-to-point correspondences, while previous methods might not. We demonstrate on a wide variety of experiments that our approach leads to significant improvement for functional map estimation by helping to reduce the number of necessary descriptor constraints by an order of magnitude, even given an increase in the size of the reduced basis.
Simulation-Ready Hair Capture
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Hu, Liwen; Bradley, Derek; Li, Hao; Beeler, Thabo; Loic Barthe and Bedrich Benes
Physical simulation has long been the approach of choice for generating realistic hair animations in CG. A constant drawback of simulation, however, is the necessity to manually set the physical parameters of the simulation model in order to get the desired dynamic behavior. To alleviate this, researchers have begun to explore methods for reconstructing hair from the real world and even to estimate the corresponding simulation parameters through the process of inversion. So far, however, these methods have had limited applicability, because dynamic hair capture can only be played back without the ability to edit, and solving for simulation parameters can only be accomplished for static hairstyles, ignoring the dynamic behavior. We present the first method for capturing dynamic hair and automatically determining the physical properties for simulating the observed hairstyle in motion. Since our dynamic inversion is agnostic to the simulation model, the proposed method applies to virtually any hair simulation technique, which we demonstrate using two state-of-the-art hair simulation models. The output of our method is a fully simulation-ready hairstyle, consisting of both the static hair geometry as well as its physical properties. The hairstyle can be easily edited by adding additional external forces, changing the head motion, or re-simulating in completely different environments, all while remaining faithful to the captured hairstyle.
Makeup Lamps: Live Augmentation of Human Faces via Projection
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Bermano, Amit Haim; Billeter, Markus; Iwai, Daisuke; Grundhöfer, Anselm; Loic Barthe and Bedrich Benes
We propose the first system for live dynamic augmentation of human faces. Using projector-based illumination, we alter the appearance of human performers during novel performances. The key challenge of live augmentation is latency - an image is generated according to a specific pose, but is displayed on a different facial configuration by the time it is projected. Therefore, our system aims at reducing latency during every step of the process, from capture, through processing, to projection. Using infrared illumination, an optically and computationally aligned high-speed camera detects facial orientation as well as expression. The estimated expression blendshapes are mapped onto a lower dimensional space, and the facial motion and non-rigid deformation are estimated, smoothed and predicted through adaptive Kalman filtering. Finally, the desired appearance is generated interpolating precomputed offset textures according to time, global position, and expression. We have evaluated our system through an optimized CPU and GPU prototype, and demonstrated successful low latency augmentation for different performers and performances with varying facial play and motion speed. In contrast to existing methods, the presented system is the first method which fully supports dynamic facial projection mapping without the requirement of any physical tracking markers and incorporates facial expressions.
DeepGarment: 3D Garment Shape Estimation from a Single Image
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Danerek, Radek; Dibra, Endri; Öztireli, A. Cengiz; Ziegler, Remo; Gross, Markus; Loic Barthe and Bedrich Benes
3D garment capture is an important component for various applications such as free-view point video, virtual avatars, online shopping, and virtual cloth fitting. Due to the complexity of the deformations, capturing 3D garment shapes requires controlled and specialized setups. A viable alternative is image-based garment capture. Capturing 3D garment shapes from a single image, however, is a challenging problem and the current solutions come with assumptions on the lighting, camera calibration, complexity of human or mannequin poses considered, and more importantly a stable physical state for the garment and the underlying human body. In addition, most of the works require manual interaction and exhibit high run-times. We propose a new technique that overcomes these limitations, making garment shape estimation from an image a practical approach for dynamic garment capture. Starting from synthetic garment shape data generated through physically based simulations from various human bodies in complex poses obtained through Mocap sequences, and rendered under varying camera positions and lighting conditions, our novel method learns a mapping from rendered garment images to the underlying 3D garment model. This is achieved by training Convolutional Neural Networks (CNN-s) to estimate 3D vertex displacements from a template mesh with a specialized loss function. We illustrate that this technique is able to recover the global shape of dynamic 3D garments from a single image under varying factors such as challenging human poses, self occlusions, various camera poses and lighting conditions, at interactive rates. Improvement is shown if more than one view is integrated. Additionally, we show applications of our method to videos.
Geometric Stiffness for Real-time Constrained Multibody Dynamics
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Andrews, Sheldon; Teichmann, Marek; Kry, Paul G.; Loic Barthe and Bedrich Benes
This paper focuses on the stable and efficient simulation of articulated rigid body systems for real-time applications. Specifically, we focus on the use of geometric stiffness, which can dramatically increase simulation stability. We examine several numerical problems with the inclusion of geometric stiffness in the equations of motion, as proposed by previous work, and address these issues by introducing a novel method for efficiently building the linear system. This offers improved tractability and numerical efficiency. Furthermore, geometric stiffness tends to significantly dissipate kinetic energy. We propose an adaptive damping scheme, inspired by the geometric stiffness, that uses a stability criterion based on the numerical integrator to determine the amount of non-constitutive damping required to stabilize the simulation. With this approach, not only is the dynamical behavior better preserved, but the simulation remains stable for mass ratios of 1,000,000-to-1 at time steps up to 0.1 s. We present a number of challenging scenarios to demonstrate that our method improves efficiency, and that it increases stability by orders of magnitude compared to previous work.
Flow-Induced Inertial Steady Vector Field Topology
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Günther, Tobias; Gross, Markus; Loic Barthe and Bedrich Benes
Traditionally, vector field visualization is concerned with 2D and 3D flows. Yet, many concepts can be extended to general dynamical systems, including the higher-dimensional problem of modeling the motion of finite-sized objects in fluids. In the steady case, the trajectories of these so-called inertial particles appear as tangent curves of a 4D or 6D vector field. These higher-dimensional flows are difficult to map to lower-dimensional spaces, which makes their visualization a challenging problem. We focus on vector field topology, which allows scientists to study asymptotic particle behavior. As recent work on the 2D case has shown, both extraction and classification of isolated critical points depend on the underlying particle model. In this paper, we aim for a model-independent classification technique, which we apply to two different particle models in not only 2D, but also 3D cases. We show that the classification can be done by performing an eigenanalysis of the spatial derivatives' velocity subspace of the higher-dimensional 4D or 6D flow. We construct glyphs that depict not only the types of critical points, but also encode the directional information given by the eigenvectors. We show that the eigenvalues and eigenvectors of the inertial phase space have sufficient symmetries and structure so that they can be depicted in 2D or 3D, instead of 4D or 6D.
Gradient-based Steering for Vision-based Crowd Simulation Algorithms
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Dutra, Teofilo B.; Marques, Ricardo; Cavalcante-Neto, Joaquim Bento; Vidal, Creto A.; Pettré, Julien; Loic Barthe and Bedrich Benes
Most recent crowd simulation algorithms equip agents with a synthetic vision component for steering. They offer promising perspectives through a more realistic simulation of the way humans navigate according to their perception of the surrounding environment. In this paper, we propose a new perception/motion loop to steering agents along collision free trajectories that significantly improves the quality of vision-based crowd simulators. In contrast with solutions where agents avoid collisions in a purely reactive (binary) way, we suggest exploring the full range of possible adaptations and retaining the locally optimal one. To this end, we introduce a cost function, based on perceptual variables, which estimates an agent's situation considering both the risks of future collision and a desired destination. We then compute the partial derivatives of that function with respect to all possible motion adaptations. The agent then adapts its motion by following the gradient. This paper has thus two main contributions: the definition of a general purpose control scheme for steering synthetic vision-based agents; and the proposition of cost functions for evaluating the perceived danger of the current situation. We demonstrate improvements in several cases.
Interactive Modeling and Authoring of Climbing Plants
(The Eurographics Association and John Wiley & Sons Ltd., 2017) Hädrich, Torsten; Benes, Bedrich; Deussen, Oliver; Pirk, Sören; Loic Barthe and Bedrich Benes
We present a novel system for the interactive modeling of developmental climbing plants with an emphasis on efficient control and plausible physics response. A plant is represented by a set of connected anisotropic particles that respond to the surrounding environment and to their inner state. Each particle stores biological and physical attributes that drive growth and plant adaptation to the environment such as light sensitivity, wind interaction, and physical obstacles. This representation allows for the efficient modeling of external effects that can be induced at any time without prior analysis of the plant structure. In our framework we exploit this representation to provide powerful editing capabilities that allow to edit a plant with respect to its structure and its environment while maintaining a biologically plausible appearance. Moreover, we couple plants with Lagrangian fluid dynamics and model advanced effects, such as the breaking and bending of branches. The user can thus interactively drag and prune branches or seed new plants in dynamically changing environments. Our system runs in real-time and supports up to 20 plant instances with 25k branches in parallel. The effectiveness of our approach is demonstrated through a number of interactive experiments, including modeling and animation of different species of climbing plants on complex support structures.

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