EG 2018 - Short Papers

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Animation and Simulation
Time-Reversed Art Directable Smoke Simulation
Jeremy Oborn, Sean Flynn, Parris Egbert, and Seth Holladay
Rigid Body Joints in Real-Time Unified Particle Physics
Bojan Lovrovic and Zeljka Mihajlovic
Reduction of CPU-GPU Synchronization Overhead for Accelerating Implicit Clothing Simulator
Sangbin Lee, Donghan Ryu, and Hyeong-Seok Ko
Kinder-Gator: The UF Kinect Database of Child and Adult Motion
Aishat Aloba, Gianne Flores, Julia Woodward, Alex Shaw, Amanda Castonguay, Isabella Cuba, Yuzhu Dong, Eakta Jain, and Lisa Anthony
Imaging, Video, and Rendering
Optimized Sampling for View Interpolation in Light Fields with Overlapping Patches
David C. Schedl and Oliver Bimber
Halftone Pattern: A New Steganographic Approach
Leandro Cruz, Bruno Patrão, and Nuno Gonçalves
Raw Point Cloud Deferred Shading Through Screen Space Pyramidal Operators
Hassan Bouchiba, Jean-Emmanuel Deschaud, and François Goulette
Accelerating Sphere Tracing
Csaba Bálint and Gábor Valasek
Modeling
Expressive Curve Editing with the Sigma Lognormal Model
Daniel Berio, Frederic Fol Leymarie, and Réjean Plamondon
Smooth Blended Subdivision Shading
Jelle Bakker, Pieter J. Barendrecht, and Jiri Kosinka
Iterative Carving for Self-supporting 3D Printed Cavities
Samuel Hornus and Sylvain Lefebvre
A Comparison of GPU Tessellation Strategies for Multisided Patches
Gerben Jan Hettinga, Pieter J. Barendrecht, and Jiri Kosinka
Methods and Applications, User Studies
A Preliminary Investigation into the Impact of Training for Example-Based Facial Blendshape Creation
Emma Carrigan, Ludovic Hoyet, Rachel McDonnell, and Quentin Avril
Arm Swinging vs Treadmill: A Comparison Between Two Techniques for Locomotion in Virtual Reality
Davide Calandra, Michele Billi, Fabrizio Lamberti, Andrea Sanna, and Romano Borchiellini
Accurate Control of a Pan-tilt System Based on Parameterization of Rotational Motion
JungHyun Byun, SeungHo Chae, and TackDon Han
Creating New Chinese Fonts based on Manifold Learning and Adversarial Networks
Yuan Guo, Zhouhui Lian, Yingmin Tang, and Jianguo Xiao

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    EUROGRAPHICS 2018: Short Papers Frontmatter
    (Eurographics Association, 2018) Diamanti, Olga; Vaxman, Amir; Diamanti, Olga; Vaxman, Amir
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    Time-Reversed Art Directable Smoke Simulation
    (The Eurographics Association, 2018) Oborn, Jeremy; Flynn, Sean; Egbert, Parris; Holladay, Seth; Diamanti, Olga and Vaxman, Amir
    Physics-based fluid simulation often produces unpredictable behavior that is difficult for artists to control. We present a new method for art directing smoke animation using time-reversed simulation. Given a final fluid configuration, our method steps backward in time generating a sequence that, when played forward, is visually similar to traditional forward simulations. This allows artists to create simulations with fast turnaround times that match an exact art-directed shape at any timestep of the simulation. We address a number of challenges associated with time-reversal including the problem of decreasing entropy.
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    Reduction of CPU-GPU Synchronization Overhead for Accelerating Implicit Clothing Simulator
    (The Eurographics Association, 2018) Lee, Sangbin; Ryu, Donghan; Ko, Hyeong-Seok; Diamanti, Olga and Vaxman, Amir
    When trying to make the conjugate gradient (CG) method exploit GPU technology, this paper notes that the communication between CPU and GPU to transfer the residual value and waiting for the CPU's decision whether to continue further iterations is a new source of delay that has been overlooked and turns out not negligible. By examining the residual decrease pattern in log scale, this paper proposes so-called the Secant Lazy Residual Evaluation (Secant LRE) method to skip needless synchronization. We experimented the method for a clothing simulator and found that the proposed method reduces the sync overhead significantly, leading to 10 60% performance gain.
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    Rigid Body Joints in Real-Time Unified Particle Physics
    (The Eurographics Association, 2018) Lovrovic, Bojan; Mihajlovic, Zeljka; Diamanti, Olga and Vaxman, Amir
    In this paper, we propose a physically-based method for a rigid body joint simulation. The proposed solution is based on the unified particle physics engine, a simulator that uses only particles for all the dynamic bodies. Such engines are implemented on the GPU and they simulate fluids, rigid bodies or deform-able materials like cloth or ropes. To support more complex systems like skeletal simulation, we show a joint implementation that is intuitive and unique to this environment. Four types of joints will be shown, as well as the necessary details about the rigid body data structure. This will enable the construction of a popular method called ragdoll. Lastly, a performance measurement and a comparison with alternatives will be given.
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    Kinder-Gator: The UF Kinect Database of Child and Adult Motion
    (The Eurographics Association, 2018) Aloba, Aishat; Flores, Gianne; Woodward, Julia; Shaw, Alex; Castonguay, Amanda; Cuba, Isabella; Dong, Yuzhu; Jain, Eakta; Anthony, Lisa; Diamanti, Olga and Vaxman, Amir
    Research has suggested that children's whole-body motions are different from those of adults. However, research on children's motions, and how these motions differ from those of adults, is limited. One possible reason for this limited research is that there are few motion capture (mocap) datasets for children, with most datasets focusing on adults instead. There are even fewer datasets that have both children's and adults' motions to allow for comparison between them. To address these problems, we present Kinder-Gator, a new dataset of ten children and ten adults performing whole-body motions in front of the Kinect v1.0. The data contains RGB and 3D joint positions for 58 motions, such as wave, walk in place, kick, and point, which have been manually labeled according to the category of the participant (child vs. adult), and the motion being performed. We believe this dataset will be useful in supporting research and applications in animation and whole-body motion recognition and interaction.
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    Halftone Pattern: A New Steganographic Approach
    (The Eurographics Association, 2018) Cruz, Leandro; Patrão, Bruno; Gonçalves, Nuno; Diamanti, Olga and Vaxman, Amir
    In general, an image is worth a thousand words, but sometimes, words are the most efficient tool to communicate some information. Thereupon, in this work, we will present an approach for combining the visual appeal of images with the communication power of words. Our method is a steganographic technique to hide a textual information into an image. It is inspired by the use of dithering to create halftone images. It begins from a base image and creates the coded image by associating each base image pixel to a set of two-colors pixels (halftone) forming an appropriate pattern. The coded image is a machine readable information, with good aesthetic, secure and containing data redundancy and compression. Thus, it can be used in a variety of applications.
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    Optimized Sampling for View Interpolation in Light Fields with Overlapping Patches
    (The Eurographics Association, 2018) Schedl, David C.; Bimber, Oliver; Diamanti, Olga and Vaxman, Amir
    Optimized sampling masks that reduce the complexity of camera arrays while preserving the quality of light fields captured at high directional sampling resolution are presented. We propose a new quality metric that is based on sampling-theoretic considerations, a new mask estimation approach that reduces the search space by applying regularity and symmetry constraints, and an enhanced upsampling technique using compressed sensing that supports maximal patch overlap. Our approach out-beats state-of-the-art view-interpolation techniques for light fields and does not rely on depth reconstruction.
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    Raw Point Cloud Deferred Shading Through Screen Space Pyramidal Operators
    (The Eurographics Association, 2018) Bouchiba, Hassan; Deschaud, Jean-Emmanuel; Goulette, François; Diamanti, Olga and Vaxman, Amir
    We present a novel real-time raw point cloud rendering algorithm based on efficient screen-space pyramidal operators. Our method is based on a pyramidal occlusion-based hidden point removal operator followed by a pyramidal reconstruction by the pull push algorithm. Then a new pyramidal smooth normals estimator enables subsequent deferred shading. We demonstrate on various real-world complex objects and scenes that our method achieves better visual results and is one order of magnitude more efficient comparing to state of the art algorithms.
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    Smooth Blended Subdivision Shading
    (The Eurographics Association, 2018) Bakker, Jelle; Barendrecht, Pieter J.; Kosinka, Jiri; Diamanti, Olga and Vaxman, Amir
    The concept known as subdivision shading aims at improving the shading of subdivision surfaces. It is based on the subdivision of normal vectors associated with the control net of the surface. By either using the resulting subdivided normal field directly, or blending it with the normal field of the limit surface, renderings of higher visual smoothness can be obtained. In this work we propose a different and more versatile approach to blend the two normal fields, yielding not only better results, but also a proof that our blended normal field is C1.
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    Accelerating Sphere Tracing
    (The Eurographics Association, 2018) Bálint, Csaba; Valasek, Gábor; Diamanti, Olga and Vaxman, Amir
    This paper presents two performance improvements on sphere tracing. First, a sphere tracing variant designed to take optimal step sizes near planar surfaces is proposed. We demonstrate how relaxation is used to make this method applicable to sphere tracing arbitrary geometries and compare its performance to classical (by Hart) and relaxed (Keinert et al.) sphere tracing in rendering various scenes. The method is also general in the sense that it can be applied in any scenario that requires the computation of ray-surface intersections. Our second contribution is a multi-resolution rendering strategy that can be used with any sphere tracing variant. By starting from a lower resolution and gradually increasing it, render times can be reduced.
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    Expressive Curve Editing with the Sigma Lognormal Model
    (The Eurographics Association, 2018) Berio, Daniel; Leymarie, Frederic Fol; Plamondon, Réjean; Diamanti, Olga and Vaxman, Amir
    We describe a practical application of the Sigma Lognormal model of handwriting movements for computer graphics applications that require the interactive or procedural definition of artistic or calligraphic traces. The method allows to easily edit curves with physiologically plausible kinematics that can be exploited in order to generate expressive brush renderings, natural looking stroke animations and easily generate stylistic variations of a trace.
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    Iterative Carving for Self-supporting 3D Printed Cavities
    (The Eurographics Association, 2018) Hornus, Samuel; Lefebvre, Sylvain; Diamanti, Olga and Vaxman, Amir
    Additive manufacturing technologies fabricate objects layer by layer, adding material on top of already solidified layers. A key challenge is to ensure that there is always material below, for otherwise added material simply falls under the effect of gravity. This is a critical issue with most technologies, and with fused filament in particular. In this work we investigate how to compute as large as possible empty cavities which boundaries are self-supporting. Our technique is based on an iterated carving algorithm, that is fast to compute and produces nested sets of inner walls. The walls have exactly the minimal printable thickness of the manufacturing process everywhere. Remarkably, our technique is out-of-core, sweeping through the model from the top down. Using our approach, we can print large objects using as little as a single filament thickness for the boundary, providing one order of magnitude reduction in print time and material use while guaranteeing printability.
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    A Comparison of GPU Tessellation Strategies for Multisided Patches
    (The Eurographics Association, 2018) Hettinga, Gerben Jan; Barendrecht, Pieter J.; Kosinka, Jiri; Diamanti, Olga and Vaxman, Amir
    We propose an augmentation of the traditional tessellation pipeline with several different strategies that efficiently render multisided patches using generalised barycentric coordinates. The strategies involve different subdivision steps and the usage of textures. In addition, we show that adaptive tessellation techniques naturally extend to some of these strategies whereas others need a slight adjustment. The technique of Loop et al. [LSNC09], commonly known as ACC-2, is extended to multisided faces to illustrate the effectiveness of multisided techniques. A performance and quality comparison is made between the different strategies and remarks on the techniques and implementation details are provided.
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    Arm Swinging vs Treadmill: A Comparison Between Two Techniques for Locomotion in Virtual Reality
    (The Eurographics Association, 2018) Calandra, Davide; Billi, Michele; Lamberti, Fabrizio; Sanna, Andrea; Borchiellini, Romano; Diamanti, Olga and Vaxman, Amir
    When it comes to locomotion in Virtual Reality (VR), a wide range of different techniques has been proposed in the scientific literature or as commercial products. However, the best choice for a specific application is still not immediate, being each technique characterized by different advantages and drawbacks. The present work reports on the results of a user study-based comparison between two methods: a locomotion treadmill, which supports omni-directional movements through walking in place over a hardware device, and Arm Swinging, which recognizes movement from the swinging back and forth of the user's arms (e.g., gathered by sensors embedded in hand controllers). Experiments have been carried out in a realistic immersive VR scenario, which requested users to respond to a fire emergency in a road tunnel by moving and interacting with the environment.
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    Accurate Control of a Pan-tilt System Based on Parameterization of Rotational Motion
    (The Eurographics Association, 2018) Byun, JungHyun; Chae, SeungHo; Han, TackDon; Diamanti, Olga and Vaxman, Amir
    A pan-tilt camera system has been adopted by a variety of fields since it can cover a wide range of region compared to a single fixated camera setup. Yet many studies rely on factory-assembled and calibrated platforms and assume an ideal rotation where rotation axes are perfectly aligned with the optical axis of the local camera. However, in a user-created setup where a pan-tilting mechanism is arbitrarily assembled, the kinematic configurations may be inaccurate or unknown, violating ideal rotation. These discrepancies in the model with the real physics result in erroneous servo manipulation of the pan-tilting system. In this paper, we propose an accurate control mechanism for arbitrarily-assembled pan-tilt camera systems. The proposed method formulates pan-tilt rotations as motion along great circle trajectories and calibrates its model parameters, such as positions and vectors of rotation axes, in 3D space. Then, one can accurately servo pan-tilt rotations with pose estimation from inverse kinematics of their transformation. The comparative experiment demonstrates out-performance of the proposed method, in terms of accurately localizing target points in world coordinates, after being rotated from their captured camera frames.
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    A Preliminary Investigation into the Impact of Training for Example-Based Facial Blendshape Creation
    (The Eurographics Association, 2018) Carrigan, Emma; Hoyet, Ludovic; McDonnell, Rachel; Avril, Quentin; Diamanti, Olga and Vaxman, Amir
    Our work is a perceptual study into the effects of training poses on the Example-Based Facial Rigging (EBFR) method. We analyse the output of EBFR given a set of training poses to see how well the results reproduced our ground truth actor scans compared to a Deformation Transfer approach. While EBFR produced better results overall, there were cases that did not see any improvement. While some of these results may be explained by lack of sufficient training poses for the area of the face in question, we found that certain lip poses were not improved by training, despite a large number of mouth training poses supplied.
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    Creating New Chinese Fonts based on Manifold Learning and Adversarial Networks
    (The Eurographics Association, 2018) Guo, Yuan; Lian, Zhouhui; Tang, Yingmin; Xiao, Jianguo; Diamanti, Olga and Vaxman, Amir
    The design of fonts, especially Chinese fonts, is known as a tough task that requires considerable time and professional skills. In this paper, we propose a method to easily generate Chinese font libraries in new styles based on manifold learning and adversarial networks. Starting from a number of existing fonts that cover various styles, we firstly use convolutional neural networks to obtain the representation features of these fonts, and then build a font manifold via non-linear mapping. Using the font manifold, we can interpolate and move between those existing fonts to get new font features, which are then fed into a generative network learned via adversarial training to generate the whole new font libraries. Experimental results demonstrate that high-quality Chinese fonts in various new styles against existing ones can be efficiently generated using our method.