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Showing papers in "ACM Transactions on Graphics in 2016"


Journal ArticleDOI
TL;DR: In this article, an image descriptor accounting for the local semantics of an image is introduced to model local adjustments that depend on image semantics, which yields results that are qualitatively and quantitatively better than previous work.
Abstract: Photo retouching enables photographers to invoke dramatic visual impressions by artistically enhancing their photos through stylistic color and tone adjustments. However, it is also a time-consuming and challenging task that requires advanced skills beyond the abilities of casual photographers. Using an automated algorithm is an appealing alternative to manual work, but such an algorithm faces many hurdles. Many photographic styles rely on subtle adjustments that depend on the image content and even its semantics. Further, these adjustments are often spatially varying. Existing automatic algorithms are still limited and cover only a subset of these challenges. Recently, deep learning has shown unique abilities to address hard problems. This motivated us to explore the use of deep neural networks (DNNs) in the context of photo editing. In this article, we formulate automatic photo adjustment in a manner suitable for this approach. We also introduce an image descriptor accounting for the local semantics of an image. Our experiments demonstrate that training DNNs using these descriptors successfully capture sophisticated photographic styles. In particular and unlike previous techniques, it can model local adjustments that depend on image semantics. We show that this yields results that are qualitatively and quantitatively better than previous work.

277 citations


Journal ArticleDOI
TL;DR: A novel approach for the automatic creation of a personalized high-quality 3D face rig of an actor from just monocular video data, based on three distinct layers that allow the actor's facial shape as well as capture his person-specific expression characteristics at high fidelity, ranging from coarse-scale geometry to fine-scale static and transient detail on the scale of folds and wrinkles.
Abstract: We present a novel approach for the automatic creation of a personalized high-quality 3D face rig of an actor from just monocular video data (e.g., vintage movies). Our rig is based on three distinct layers that allow us to model the actor’s facial shape as well as capture his person-specific expression characteristics at high fidelity, ranging from coarse-scale geometry to fine-scale static and transient detail on the scale of folds and wrinkles. At the heart of our approach is a parametric shape prior that encodes the plausible subspace of facial identity and expression variations. Based on this prior, a coarse-scale reconstruction is obtained by means of a novel variational fitting approach. We represent person-specific idiosyncrasies, which cannot be represented in the restricted shape and expression space, by learning a set of medium-scale corrective shapes. Fine-scale skin detail, such as wrinkles, are captured from video via shading-based refinement, and a generative detail formation model is learned. Both the medium- and fine-scale detail layers are coupled with the parametric prior by means of a novel sparse linear regression formulation. Once reconstructed, all layers of the face rig can be conveniently controlled by a low number of blendshape expression parameters, as widely used by animation artists. We show captured face rigs and their motions for several actors filmed in different monocular video formats, including legacy footage from YouTube, and demonstrate how they can be used for 3D animation and 2D video editing. Finally, we evaluate our approach qualitatively and quantitatively and compare to related state-of-the-art methods.

267 citations


Journal ArticleDOI
TL;DR: It is concluded that off-the-shelf TOF cameras can look around corners and that performance depends on two primary factors: camera modulation frequency and the width of the specular lobe (“shininess”) of the wall.
Abstract: We explore the question of whether phase-based time-of-flight (TOF) range cameras can be used for looking around corners and through scattering diffusers. By connecting TOF measurements with theory from array signal processing, we conclude that performance depends on two primary factors: camera modulation frequency and the width of the specular lobe (“shininess”) of the wall. For purely Lambertian walls, commodity TOF sensors achieve resolution on the order of meters between targets. For seemingly diffuse walls, such as posterboard, the resolution is drastically reduced, to the order of 10cm. In particular, we find that the relationship between reflectance and resolution is nonlinear—a slight amount of shininess can lead to a dramatic improvement in resolution. Since many realistic scenes exhibit a slight amount of shininess, we believe that off-the-shelf TOF cameras can look around corners.

118 citations


Journal ArticleDOI
TL;DR: A combined primal-dual surface representation enables the development of developables as splines and the nonlinear conditions relating to developability and curved folds as quadratic equations to utilize a constraint solver.
Abstract: We present a new approach to geometric modeling with developable surfaces and the design of curved-creased origami. We represent developables as splines and express the nonlinear conditions relating to developability and curved folds as quadratic equations. This allows us to utilize a constraint solver, which may be described as energy-guided projection onto the constraint manifold, and which is fast enough for interactive modeling. Further, a combined primal-dual surface representation enables us to robustly and quickly solve approximation problems.

116 citations


Journal ArticleDOI
TL;DR: This work presents a method for learning robust feedback strategies around given motion capture clips as well as the transition paths between clips, and develops a synthesis framework for the development of robust controllers with a minimal amount of prior knowledge.
Abstract: The difficulty of developing control strategies has been a primary bottleneck in the adoption of physics-based simulations of human motion. We present a method for learning robust feedback strategies around given motion capture clips as well as the transition paths between clips. The output is a control graph that supports real-time physics-based simulation of multiple characters, each capable of a diverse range of robust movement skills, such as walking, running, sharp turns, cartwheels, spin-kicks, and flips. The control fragments that compose the control graph are developed using guided learning. This leverages the results of open-loop sampling-based reconstruction in order to produce state-action pairs that are then transformed into a linear feedback policy for each control fragment using linear regression. Our synthesis framework allows for the development of robust controllers with a minimal amount of prior knowledge.

114 citations


Journal ArticleDOI
TL;DR: The key to make simulation programmers more productive at developing portable and performant code is to introduce new linguistic abstractions, as in rendering and image processing.
Abstract: Writing highly performant simulations requires a lot of human effort to optimize for an increasingly diverse set of hardware platforms, such as multi-core CPUs, GPUs, and distributed machines. Since these optimizations cut across both the design of geometric data structures and numerical linear algebra, code reusability and portability is frequently sacrificed for performance.We believe the key to make simulation programmers more productive at developing portable and performant code is to introduce new linguistic abstractions, as in rendering and image processing. In this perspective, we distill the core ideas from our two languages, Ebb and Simit, that are published in this journal.

98 citations


Journal ArticleDOI
TL;DR: In this paper, a femtosecond laser is used for rendering aerial and volumetric graphics using femto-cond (FSL) laser sources, which can produce holograms using spatial light modulation technology and scanning of a laser beam by a galvano mirror.
Abstract: We present a method of rendering aerial and volumetric graphics using femtosecond lasers. A high-intensity laser excites physical matter to emit light at an arbitrary three-dimensional position. Popular applications can thus be explored, especially because plasma induced by a femtosecond laser is less harmful than that generated by a nanosecond laser. There are two methods of rendering graphics with a femtosecond laser in air: producing holograms using spatial light modulation technology and scanning of a laser beam by a galvano mirror. The holograms and workspace of the system proposed here occupy a volume of up to 1 cm3; however, this size is scalable depending on the optical devices and their setup. This article provides details of the principles, system setup, and experimental evaluation, and discusses the scalability, design space, and applications of this system. We tested two laser sources: an adjustable (30--100fs) laser that projects up to 1,000 pulses/s at an energy of up to 7mJ/pulse and a 269fs laser that projects up to 200,000 pulses/s at an energy of up to 50μJ/pulse. We confirmed that the spatiotemporal resolution of volumetric displays implemented using these laser sources is 4,000 and 200,000 dots/s, respectively. Although we focus on laser-induced plasma in air, the discussion presented here is also applicable to other rendering principles such as fluorescence and microbubbles in solid or liquid materials.

90 citations


Journal ArticleDOI
TL;DR: This article uses a user’s personal photo collection to find a “good” set of reference eyes and transfer them onto a target image and develops a comprehensive pipeline of three-dimensional face estimation, image warping, relighting, image harmonization, automatic segmentation, and image compositing in order to achieve highly believable results.
Abstract: Closed eyes and look-aways can ruin precious moments captured in photographs. In this article, we present a new framework for automatically editing eyes in photographs. We leverage a user’s personal photo collection to find a “good” set of reference eyes and transfer them onto a target image. Our example-based editing approach is robust and effective for realistic image editing. A fully automatic pipeline for realistic eye editing is challenging due to the unconstrained conditions under which the face appears in a typical photo collection. We use crowd-sourced human evaluations to understand the aspects of the target-reference image pair that will produce the most realistic results. We subsequently train a model that automatically selects the top-ranked reference candidate(s) by narrowing the gap in terms of pose, local contrast, lighting conditions, and even expressions. Finally, we develop a comprehensive pipeline of three-dimensional face estimation, image warping, relighting, image harmonization, automatic segmentation, and image compositing in order to achieve highly believable results. We evaluate the performance of our method via quantitative and crowd-sourced experiments.

87 citations


Journal ArticleDOI
TL;DR: An efficient algorithm to automatically segment a static foreground object from highly cluttered background in light fields to exploit high spatio-angular sampling on the order of thousands of input frames, such that new structures are revealed due to the increased coherence in the data.
Abstract: Precise object segmentation in image data is a fundamental problem with various applications, including 3D object reconstruction. We present an efficient algorithm to automatically segment a static foreground object from highly cluttered background in light fields. A key insight and contribution of our article is that a significant increase of the available input data can enable the design of novel, highly efficient approaches. In particular, the central idea of our method is to exploit high spatio-angular sampling on the order of thousands of input frames, for example, captured as a hand-held video, such that new structures are revealed due to the increased coherence in the data. We first show how purely local gradient information contained in slices of such a dense light field can be combined with information about the camera trajectory to make efficient estimates of the foreground and background. These estimates are then propagated to textureless regions using edge-aware filtering in the epipolar volume. Finally, we enforce global consistency in a gathering step to derive a precise object segmentation in both 2D and 3D space, which captures fine geometric details even in very cluttered scenes. The design of each of these steps is motivated by efficiency and scalability, allowing us to handle large, real-world video datasets on a standard desktop computer. We demonstrate how the results of our method can be used for considerably improving the speed and quality of image-based 3D reconstruction algorithms, and we compare our results to state-of-the-art segmentation and multiview stereo methods.

74 citations


Journal ArticleDOI
TL;DR: This work introduces a new approach for segmentation and label transfer in sketches that substantially improves the state of the art, and uses a Conditional Random Field to find the most probable global configuration.
Abstract: We introduce a new approach for segmentation and label transfer in sketches that substantially improves the state of the art. We build on successful techniques to find how likely each segment is to belong to a label, and use a Conditional Random Field to find the most probable global configuration. Our method is trained fully on the sketch domain, such that it can handle abstract sketches that are very far from 3D meshes. It also requires a small quantity of annotated data, which makes it easily adaptable to new datasets. The testing phase is completely automatic, and our performance is comparable to state-of-the-art methods that require manual tuning and a considerable amount of previous annotation [Huang et al. 2014].

64 citations


Journal ArticleDOI
TL;DR: This work presents a new rotation-invariant deformation representation and a novel reconstruction algorithm to accurately reconstruct the positions and local rotations simultaneously, and proposes novel data-driven approaches to mesh deformation and non-rigid registration of deformable objects.
Abstract: Effectively characterizing the behavior of deformable objects has wide applicability but remains challenging. We present a new rotation-invariant deformation representation and a novel reconstruction algorithm to accurately reconstruct the positions and local rotations simultaneously. Meshes can be very efficiently reconstructed from our representation by matrix pre-decomposition, while, at the same time, hard or soft constraints can be flexibly specified with only positions of handles needed. Our approach is thus particularly suitable for constrained deformations guided by examples, providing significant benefits over state-of-the-art methods. Based on this, we further propose novel data-driven approaches to mesh deformation and non-rigid registration of deformable objects. Both problems are formulated consistently as finding an optimized model in the shape space that satisfies boundary constraints, either specified by the user, or according to the scan. By effectively exploiting the knowledge in the shape space, our method produces realistic deformation results in real-time and produces high quality registrations from a template model to a single noisy scan captured using a low-quality depth camera, outperforming state-of-the-art methods.

Journal ArticleDOI
TL;DR: Simit is a new language for physical simulations that lets the programmer view the system both as a linked data structure in the form of a hypergraph and as a set of global vectors, matrices, and tensors depending on what is convenient at any given time.
Abstract: With existing programming tools, writing high-performance simulation code is labor intensive and requires sacrificing readability and portability The alternative is to prototype simulations in a high-level language like Matlab, thereby sacrificing performance The Matlab programming model naturally describes the behavior of an entire physical system using the language of linear algebra However, simulations also manipulate individual geometric elements, which are best represented using linked data structures like meshes Translating between the linked data structures and linear algebra comes at significant cost, both to the programmer and to the machine High-performance implementations avoid the cost by rephrasing the computation in terms of linked or index data structures, leaving the code complicated and monolithic, often increasing its size by an order of magnitudeIn this article, we present Simit, a new language for physical simulations that lets the programmer view the system both as a linked data structure in the form of a hypergraph and as a set of global vectors, matrices, and tensors depending on what is convenient at any given time Simit provides a novel assembly construct that makes it conceptually easy and computationally efficient to move between the two abstractions Using the information provided by the assembly construct, the compiler generates efficient in-place computation on the graph We demonstrate that Simit is easy to use: a Simit program is typically shorter than a Matlab program; that it is high performance: a Simit program running sequentially on a CPU performs comparably to hand-optimized simulations; and that it is portable: Simit programs can be compiled for GPUs with no change to the program, delivering 4 to 20× speedups over our optimized CPU code

Journal ArticleDOI
TL;DR: DisCo enables displays and cameras to communicate with each other while also displaying and capturing images for human consumption and can be widely deployed in several applications, such as advertising, pairing of displays with cell phones, tagging objects in stores and museums, and indoor navigation.
Abstract: We present DisCo, a novel display-camera communication system. DisCo enables displays and cameras to communicate with each other while also displaying and capturing images for human consumption. Messages are transmitted by temporally modulating the display brightness at high frequencies so that they are imperceptible to humans. Messages are received by a rolling shutter camera that converts the temporally modulated incident light into a spatial flicker pattern. In the captured image, the flicker pattern is superimposed on the pattern shown on the display. The flicker and the display pattern are separated by capturing two images with different exposures. The proposed system performs robustly in challenging real-world situations such as occlusion, variable display size, defocus blur, perspective distortion, and camera rotation. Unlike several existing visible light communication methods, DisCo works with off-the-shelf image sensors. It is compatible with a variety of sources (including displays, single LEDs), as well as reflective surfaces illuminated with light sources. We have built hardware prototypes that demonstrate DisCo’s performance in several scenarios. Because of its robustness, speed, ease of use, and generality, DisCo can be widely deployed in several applications, such as advertising, pairing of displays with cell phones, tagging objects in stores and museums, and indoor navigation.

Journal ArticleDOI
TL;DR: This work proposes a technique to decompose an image into layers, in which each layer represents a single-color coat of paint applied with varying opacity based on the image’s RGB-space geometry.
Abstract: In digital image editing software, layers organize images. However, layers are often not explicitly represented in the final image, and may never have existed for a scanned physical painting or a photograph. We propose a technique to decompose an image into layers. In our decomposition, each layer represents a single-color coat of paint applied with varying opacity. Our decomposition is based on the image’s RGB-space geometry. In RGB-space, the linear nature of the standard Porter-Duff [1984] “over” pixel compositing operation implies a geometric structure. The vertices of the convex hull of image pixels in RGB-space correspond to a palette of paint colors. These colors may be “hidden” and inaccessible to algorithms based on clustering visible colors. For our layer decomposition, users choose the palette size (degree of simplification to perform on the convex hull), as well as a layer order for the paint colors (vertices). We then solve a constrained optimization problem to find translucent, spatially coherent opacity for each layer, such that the composition of the layers reproduces the original image. We demonstrate the utility of the resulting decompositions for recoloring (global and local) and object insertion. Our layers can be interpreted as generalized barycentric coordinates; we compare to these and other recoloring approaches.

Journal ArticleDOI
TL;DR: Experiments show that the proposed glyph-centric approach, with learned parameters for spacing, line thickness, and pressure, produces novel images of handwriting that look hand-made to casual observers, even when printed on paper.
Abstract: There are many scenarios where we wish to imitate a specific author’s pen-on-paper handwriting style. Rendering new text in someone’s handwriting is difficult because natural handwriting is highly variable, yet follows both intentional and involuntary structure that makes a person’s style self-consistent. The variability means that naive example-based texture synthesis can be conspicuously repetitive. We propose an algorithm that renders a desired input string in an author’s handwriting. An annotated sample of the author’s handwriting is required; the system is flexible enough that historical documents can usually be used with only a little extra effort. Experiments show that our glyph-centric approach, with learned parameters for spacing, line thickness, and pressure, produces novel images of handwriting that look hand-made to casual observers, even when printed on paper.

Journal ArticleDOI
TL;DR: This work investigates the expressiveness of the microfacet model for isotropic bidirectional reflectance distribution functions (BRDFs) measured from real materials by introducing a non-parametric factor model that represents the model’s functional structure but abandons restricted parametric formulations of its factors.
Abstract: We investigate the expressiveness of the microfacet model for isotropic bidirectional reflectance distribution functions (BRDFs) measured from real materials by introducing a non-parametric factor model that represents the model’s functional structure but abandons restricted parametric formulations of its factors. We propose a new objective based on compressive weighting that controls rendering error in high-dynamic-range BRDF fits better than previous factorization approaches. We develop a simple numerical procedure to minimize this objective and handle dependencies that arise between microfacet factors. Our method faithfully captures a more comprehensive set of materials than previous state-of-the-art parametric approaches yet remains compact (3.2KB per BRDF). We experimentally validate the benefit of the microfacet model over a naive orthogonal factorization and show that fidelity for diffuse materials is modestly improved by fitting an unrestricted shadowing/masking factor. We also compare against a recent data-driven factorization approach [Bilgili et al. 2011] and show that our microfacet-based representation improves rendering accuracy for most materials while reducing storage by more than 10 ×.

Journal ArticleDOI
TL;DR: A new algorithm for dynamic late reverberation that performs high-order ray tracing from the listener against spherical sound sources and a hybrid convolution-based audio rendering technique that can process hundreds of thousands of sound paths at interactive rates are presented.
Abstract: We present an approach to generate plausible acoustic effects at interactive rates in large dynamic environments containing many sound sources. Our formulation combines listener-based backward ray tracing with sound source clustering and hybrid audio rendering to handle complex scenes. We present a new algorithm for dynamic late reverberation that performs high-order ray tracing from the listener against spherical sound sources. We achieve sublinear scaling with the number of sources by clustering distant sound sources and taking relative visibility into account. We also describe a hybrid convolution-based audio rendering technique that can process hundreds of thousands of sound paths at interactive rates. We demonstrate the performance on many indoor and outdoor scenes with up to 200 sound sources. In practice, our algorithm can compute more than 50 reflection orders at interactive rates on a multicore PC, and we observe a 5x speedup over prior geometric sound propagation algorithms.

Journal ArticleDOI
TL;DR: The method results in better scores for classical quality criteria of hexahedral-dominant meshes (hexahedral proportion, scaled Jacobian, etc.) and shows better robustness than CubeCover and its derivatives when applied to complicated industrial models.
Abstract: This article introduces a method that generates a hexahedral-dominant mesh from an input tetrahedral mesh. It follows a three-step pipeline similar to the one proposed by Carrier Baudoin et al.: (1) generate a frame field, (2) generate a pointset P that is mostly organized on a regular grid locally aligned with the frame field, and (3) generate the hexahedral-dominant mesh by recombining the tetrahedra obtained from the constrained Delaunay triangulation of P. For step (1), we use a state-of-the-art algorithm to generate a smooth frame field. For step (2), we introduce an extension of Periodic Global Parameterization to the volumetric case. As compared with other global parameterization methods (such as CubeCover), our method relaxes some global constraints to avoid creating degenerate elements, at the expense of introducing some singularities that are meshed using non-hexahedral elements. For step (3), we build on the formalism introduced by Meshkat and Talmor, fill in a gap in their proof, and provide a complete enumeration of all the possible recombinations, as well as an algorithm that efficiently detects all the matches in a tetrahedral mesh. The method is evaluated and compared with the state of the art on a database of examples with various mesh complexities, varying from academic examples to real industrial cases. Compared with the method of Carrier-Baudoin et al., the method results in better scores for classical quality criteria of hexahedral-dominant meshes (hexahedral proportion, scaled Jacobian, etc.). The method also shows better robustness than CubeCover and its derivatives when applied to complicated industrial models.

Journal ArticleDOI
TL;DR: This article introduces a discrete definition of connection on simplicial manifolds, involving closed-form continuous expressions within simplices and finite rotations across simplices, and construction of a covariant derivative is constructed through exact differentiation.
Abstract: In this article, we introduce a discrete definition of connection on simplicial manifolds, involving closed-form continuous expressions within simplices and finite rotations across simplices. The finite-dimensional parameters of this connection are optimally computed by minimizing a quadratic measure of the deviation to the (discontinuous) Levi-Civita connection induced by the embedding of the input triangle mesh, or to any metric connection with arbitrary cone singularities at vertices. From this discrete connection, a covariant derivative is constructed through exact differentiation, leading to explicit expressions for local integrals of first-order derivatives (such as divergence, curl, and the Cauchy-Riemann operator) and for L2-based energies (such as the Dirichlet energy). We finally demonstrate the utility, flexibility, and accuracy of our discrete formulations for the design and analysis of vector, n-vector, and n-direction fields.

Journal ArticleDOI
TL;DR: The purpose and contribution of this work is to describe a formal, broadly applicable, procedural, and empirically grounded association between personality and body motion and apply this association to modify a given virtual human body animation that can be represented by these formal concepts.
Abstract: A major goal of research on virtual humans is the animation of expressive characters that display distinct psychological attributes. Body motion is an effective way of portraying different personalities and differentiating characters. The purpose and contribution of this work is to describe a formal, broadly applicable, procedural, and empirically grounded association between personality and body motion and apply this association to modify a given virtual human body animation that can be represented by these formal concepts. Because the body movement of virtual characters may involve different choices of parameter sets depending on the context, situation, or application, formulating a link from personality to body motion requires an intermediate step to assist generalization. For this intermediate step, we refer to Laban Movement Analysis, which is a movement analysis technique for systematically describing and evaluating human motion. We have developed an expressive human motion generation system with the help of movement experts and conducted a user study to explore how the psychologically validated OCEAN personality factors were perceived in motions with various Laban parameters. We have then applied our findings to procedurally animate expressive characters with personality, and validated the generalizability of our approach across different models and animations via another perception study.

Journal ArticleDOI
TL;DR: A new projector architecture built around commercially available components, in which light can be steered to form images is proposed, which significantly reduces the total cost of ownership of a projector (fewer components and lower operating cost), and at the same time increases peak luminance and improves black level beyond what is practically achievable with incumbent projector technologies.
Abstract: Cinema projectors need to compete with home theater displays in terms of image quality. High frame rate and spatial resolution as well as stereoscopic 3D are common features today, but even the most advanced cinema projectors lack in-scene contrast and, more important, high peak luminance, both of which are essential perceptual attributes of images appearing realistic. At the same time, HDR image statistics suggest that the average image intensity in a controlled ambient viewing environment such as the cinema can be as low as 1p for cinematic HDR content and not often higher than 18p, middle gray in photography. Traditional projection systems form images and colors by blocking the source light from a lamp, therefore attenuating between 99p and 82p of light, on average. This inefficient use of light poses significant challenges for achieving higher peak brightness levels. In this work, we propose a new projector architecture built around commercially available components, in which light can be steered to form images. The gain in system efficiency significantly reduces the total cost of ownership of a projector (fewer components and lower operating cost), and at the same time increases peak luminance and improves black level beyond what is practically achievable with incumbent projector technologies. At the heart of this computational display technology is a new projector hardware design using phase modulation in combination with a new optimization algorithm that is capable of on-the-fly computation of freeform lens surfaces.

Journal ArticleDOI
TL;DR: Ebb is presented, a Domain-Specific Language for simulation, that runs efficiently on both CPUs and GPUs, and is evaluated by comparing it to several widely used simulations, demonstrating comparable performance to handwritten GPU code where available, and surpassing existing CPU performance optimizations by up to 9 × when no GPU code exists.
Abstract: Designing programming environments for physical simulation is challenging because simulations rely on diverse algorithms and geometric domains. These challenges are compounded when we try to run efficiently on heterogeneous parallel architectures. We present Ebb, a Domain-Specific Language (DSL) for simulation, that runs efficiently on both CPUs and GPUs. Unlike previous DSLs, Ebb uses a three-layer architecture to separate (1) simulation code, (2) definition of data structures for geometric domains, and (3) runtimes supporting parallel architectures. Different geometric domains are implemented as libraries that use a common, unified, relational data model. By structuring the simulation framework in this way, programmers implementing simulations can focus on the physics and algorithms for each simulation without worrying about their implementation on parallel computers. Because the geometric domain libraries are all implemented using a common runtime based on relations, new geometric domains can be added as needed, without specifying the details of memory management, mapping to different parallel architectures, or having to expand the runtime’s interface.We evaluate Ebb by comparing it to several widely used simulations, demonstrating comparable performance to handwritten GPU code where available, and surpassing existing CPU performance optimizations by up to 9 × when no GPU code exists.

Journal ArticleDOI
TL;DR: In this article, a grid-based signed distance function is used to interpolate smoke and liquid simulations in order to perform data-driven fluid simulations, which can be applied to details around the surface and the inherent handling of topology changes.
Abstract: We present a novel method to interpolate smoke and liquid simulations in order to perform data-driven fluid simulations. Our approach calculates a dense space-time deformation using grid-based signed-distance functions of the inputs.A key advantage of this implicit Eulerian representation is that it allows us to use powerful techniques from the optical flow area. We employ a five-dimensional optical flow solve. In combination with a projection algorithm, and residual iterations, we achieve a robust matching of the inputs. Once the match is computed, arbitrary in-between variants can be created very efficiently. To concatenate multiple long-range deformations, we propose a novel alignment technique.Our approach has numerous advantages, including automatic matches without user input, volumetric deformations that can be applied to details around the surface, and the inherent handling of topology changes. As a result, we can interpolate swirling smoke clouds, and splashing liquid simulations. We can even match and interpolate phenomena with fundamentally different physics: a drop of liquid, and a blob of heavy smoke.

Journal ArticleDOI
TL;DR: It is proved that both approaches to static analysis of masonry buildings can be viewed as equivalent, dual methods for getting the same answer to the same problem.
Abstract: We examine two widely used classes of methods for static analysis of masonry buildings: linear elasticity analysis using finite elements and equilibrium methods. It is often claimed in the literature that finite element analysis is less accurate than equilibrium analysis when it comes to masonry analysis; we examine and qualify this claimed inaccuracy, provide a systematic explanation for the discrepancy observed between their results, and present a unified formulation of the two approaches to stability analysis. We prove that both approaches can be viewed as equivalent, dual methods for getting the same answer to the same problem. We validate our observations with simulations and physical tilt experiments of structures.

Journal ArticleDOI
TL;DR: This work introduces animated sphere-meshes, which are meshes indexing a set of animated spheres, which is the first to output an animated volumetric structure to approximate animated 3D surfaces and optimizes for the sphere approximation, connectivity, and temporal coherence.
Abstract: Performance capture systems are used to acquire high-quality animated 3D surfaces, usually in form of a dense 3D triangle mesh. Extracting a more compact yet faithful representation is often desirable, but existing solutions for animated sequences are surface based, which leads to a limited approximation power in the case of extreme simplification. We introduce animated sphere-meshes, which are meshes indexing a set of animated spheres. Our solution is the first to output an animated volumetric structure to approximate animated 3D surfaces and optimizes for the sphere approximation, connectivity, and temporal coherence. As a result, our algorithm produces a multiresolution structure from which a level of simplification can be selected in real time, preserving a faithful approximation of the input, even at the coarsest levels. We demonstrate the use of animated sphere-meshes for low-cost approximate collision detection. Additionally, we propose a skinning decomposition, which automatically rigs the input mesh to the chosen level of detail. The resulting set of weights are smooth, compress the animation, and enable easy edits.

Journal ArticleDOI
TL;DR: This article introduces a method that generates a hexahedral-dominant mesh from an input tetrahedral mesh following a three-step pipeline similar to the one proposed by Carrier Baudoin et al.
Abstract: This article introduces a method that generates a hexahedral-dominant mesh from an input tetrahedral mesh. It follows a three-step pipeline similar to the one proposed by Carrier Baudoin et al.: (1...

Journal ArticleDOI
TL;DR: A novel green-screen keying method utilizing a new energy minimization-based color unmixing algorithm is proposed, which shows that the quality of the results can be generated using only one-tenth of the manual editing time that a professional compositing artist requires to process the same content.
Abstract: Due to the widespread use of compositing in contemporary feature films, green-screen keying has become an essential part of postproduction workflows. To comply with the ever-increasing quality requirements of the industry, specialized compositing artists spend countless hours using multiple commercial software tools, while eventually having to resort to manual painting because of the many shortcomings of these tools. Due to the sheer amount of manual labor involved in the process, new green-screen keying approaches that produce better keying results with less user interaction are welcome additions to the compositing artist’s arsenal. We found that—contrary to the common belief in the research community—production-quality green-screen keying is still an unresolved problem with its unique challenges. In this article, we propose a novel green-screen keying method utilizing a new energy minimization-based color unmixing algorithm. We present comprehensive comparisons with commercial software packages and relevant methods in literature, which show that the quality of our results is superior to any other currently available green-screen keying solution. It is important to note that, using the proposed method, these high-quality results can be generated using only one-tenth of the manual editing time that a professional compositing artist requires to process the same content having all previous state-of-the-art tools at one’s disposal.

Journal ArticleDOI
TL;DR: In this article, a 3D printed perforated lampshade is designed to project continuous grayscale images onto the surrounding walls, such that the combined footprints of light emanating through the holes form the target image on a nearby diffuse surface.
Abstract: We present a technique for designing three-dimensional- (3D) printed perforated lampshades that project continuous grayscale images onto the surrounding walls. Given the geometry of the lampshade and a target grayscale image, our method computes a distribution of tiny holes over the shell, such that the combined footprints of the light emanating through the holes form the target image on a nearby diffuse surface. Our objective is to approximate the continuous tones and the spatial detail of the target image to the extent possible within the constraints of the fabrication process.To ensure structural integrity, there are lower bounds on the thickness of the shell, the radii of the holes, and the minimal distances between adjacent holes. Thus, the holes are realized as thin tubes distributed over the lampshade surface. The amount of light passing through a single tube may be controlled by the tube’s radius and by its orientation (tilt angle). The core of our technique thus consists of determining a suitable configuration of the tubes: their distribution across the relevant portion of the lampshade, as well as the parameters (radius, tilt angle) of each tube. This is achieved by computing a capacity-constrained Voronoi tessellation over a suitably defined density function and embedding a tube inside the maximal inscribed circle of each tessellation cell.

Journal ArticleDOI
TL;DR: This article proposes a parallel prioritized Jacobian-based inverse kinematics algorithm that can handle complex articulated bodies at interactive frame rates and demonstrates how the GPU can further exploit fine-grain parallelism not directly available on a multicore processor.
Abstract: In this article, we present a parallel prioritized Jacobian-based inverse kinematics algorithm for multithreaded architectures. We solve damped least squares inverse kinematics using a parallel line search by identifying and sampling critical input parameters. Parallel competing execution paths are spawned for each parameter in order to select the optimum that minimizes the error criteria. Our algorithm is highly scalable and can handle complex articulated bodies at interactive frame rates. We show results on complex skeletons consisting of more than 600 degrees of freedom while being controlled using multiple end effectors. We implement the algorithm both on multicore and GPU architectures and demonstrate how the GPU can further exploit fine-grain parallelism not directly available on a multicore processor. Our implementations are 10 to 150 times faster compared to a state-of-the-art serial implementation while providing higher accuracy. We also demonstrate the scalability of the algorithm over multiple scenarios and explore the GPU implementation in detail.

Journal ArticleDOI
A. Cengiz Öztireli1
TL;DR: It is shown that significant reductions in error can be obtained by considering alternative sampling strategies instead of the commonly used random jittering or low discrepancy patterns, and lead to novel insights.
Abstract: We present a novel comprehensive approach for studying error in integral estimation with point distributions based on point process statistics. We derive exact formulae for bias and variance of integral estimates in terms of the spatial or spectral characteristics of integrands and first- and-second order product density measures of general point patterns. The formulae allow us to study and design sampling schemes adapted to different classes of integrands by analyzing the effect of sampling density, weighting, and correlations among point locations separately. We then focus on non-adaptive correlated stratified sampling patterns and specialize the formulae to derive closed-form and easy-to-analyze expressions of bias and variance for various stratified sampling strategies. Based on these expressions, we perform a theoretical error analysis for integrands involving the discontinuous visibility function. We show that significant reductions in error can be obtained by considering alternative sampling strategies instead of the commonly used random jittering or low discrepancy patterns. Our theoretical results agree with and extend various previous results, provide a unified analytic treatment of point patterns, and lead to novel insights. We validate the results with extensive experiments on benchmark integrands as well as real scenes with soft shadows.