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Now showing 1 - 10 of 253
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    Rendering and Extracting Extremal Features in 3D Fields
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Kindlmann, Gordon L.; Chiw, Charisee; Huynh, Tri; Gyulassy, Attila; Reppy, John; Bremer, Peer-Timo; Jeffrey Heer and Heike Leitte and Timo Ropinski
    Visualizing and extracting three-dimensional features is important for many computational science applications, each with their own feature definitions and data types. While some are simple to state and implement (e.g. isosurfaces), others require more complicated mathematics (e.g. multiple derivatives, curvature, eigenvectors, etc.). Correctly implementing mathematical definitions is difficult, so experimenting with new features requires substantial investments. Furthermore, traditional interpolants rarely support the necessary derivatives, and approximations can reduce numerical stability. Our new approach directly translates mathematical notation into practical visualization and feature extraction, with minimal mental and implementation overhead. Using a mathematically expressive domain-specific language, Diderot, we compute direct volume renderings and particlebased feature samplings for a range of mathematical features. Non-expert users can experiment with feature definitions without any exposure to meshes, interpolants, derivative computation, etc. We demonstrate high-quality results on notoriously difficult features, such as ridges and vortex cores, using working code simple enough to be presented in its entirety.
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    Visualization of 4D Vector Field Topology
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Hofmann, Lutz; Rieck, Bastian; Sadlo, Filip; Jeffrey Heer and Heike Leitte and Timo Ropinski
    In this paper, we present an approach to the topological analysis of four-dimensional vector fields. In analogy to traditional 2D and 3D vector field topology, we provide a classification and visual representation of critical points, together with a technique for extracting their invariant manifolds. For effective exploration of the resulting four-dimensional structures, we present a 4D camera that provides concise representation by exploiting projection degeneracies, and a 4D clipping approach that avoids self-intersection in the 3D projection. We exemplify the properties and the utility of our approach using specific synthetic cases.
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    HairControl: A Tracking Solution for Directable Hair Simulation
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Milliez, Antoine; Sumner, Robert W.; Gross, Markus; Thomaszewski, Bernhard; Thuerey, Nils and Beeler, Thabo
    We present a method for adding artistic control to physics-based hair simulation. Taking as input an animation of a coarse set of guide hairs, we constrain a subsequent higher-resolution simulation of detail hairs to follow the input motion in a spatially-averaged sense. The resulting high-resolution motion adheres to the artistic intent, but is enhanced with detailed deformations and dynamics generated by physics-based simulation. The technical core of our approach is formed by a set of tracking constraints, requiring the center of mass of a given subset of detail hair to maintain its position relative to a reference point on the corresponding guide hair. As a crucial element of our formulation, we introduce the concept of dynamicallychanging constraint targets that allow reference points to slide along the guide hairs to provide sufficient flexibility for natural deformations. We furthermore propose to regularize the null space of the tracking constraints based on variance minimization, effectively controlling the amount of spread in the hair. We demonstrate the ability of our tracking solver to generate directable yet natural hair motion on a set of targeted experiments and show its application to production-level animations.
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    Learning Physically Based Humanoid Climbing Movements
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Naderi, Kourosh; Babadi, Amin; Hämäläinen, Perttu; Thuerey, Nils and Beeler, Thabo
    We propose a novel learning-based solution for motion planning of physically-based humanoid climbing that allows for fast and robust planning of complex climbing strategies and movements, including extreme movements such as jumping. Similar to recent previous work, we combine a high-level graph-based path planner with low-level sampling-based optimization of climbing moves. We contribute through showing that neural network models of move success probability, effortfulness, and control policy can make both the high-level and low-level components more efficient and robust. The models can be trained through random simulation practice without any data. The models also eliminate the need for laboriously hand-tuned heuristics for graph search. As a result, we are able to efficiently synthesize climbing sequences involving dynamic leaps and one-hand swings, i.e. there are no limits to the movement complexity or the number of limbs allowed to move simultaneously. Our supplemental video also provides some comparisons between our AI climber and a real human climber.
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    Semantic Reconstruction: Reconstruction of Semantically Segmented 3D Meshes via Volumetric Semantic Fusion
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Jeon, Junho; Jung, Jinwoong; Kim, Jungeon; Lee, Seungyong; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    Semantic segmentation partitions a given image or 3D model of a scene into semantically meaning parts and assigns predetermined labels to the parts. With well-established datasets, deep networks have been successfully used for semantic segmentation of RGB and RGB-D images. On the other hand, due to the lack of annotated large-scale 3D datasets, semantic segmentation for 3D scenes has not yet been much addressed with deep learning. In this paper, we present a novel framework for generating semantically segmented triangular meshes of reconstructed 3D indoor scenes using volumetric semantic fusion in the reconstruction process. Our method integrates the results of CNN-based 2D semantic segmentation that is applied to the RGB-D stream used for dense surface reconstruction. To reduce the artifacts from noise and uncertainty of single-view semantic segmentation, we introduce adaptive integration for the volumetric semantic fusion and CRF-based semantic label regularization. With these methods, our framework can easily generate a high-quality triangular mesh of the reconstructed 3D scene with dense (i.e., per-vertex) semantic labels. Extensive experiments demonstrate that our semantic segmentation results of 3D scenes achieves the state-of-the-art performance compared to the previous voxel-based and point cloud-based methods.
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    Easy Generation of Facial Animation Using Motion Graphs
    (© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Serra, J.; Cetinaslan, O.; Ravikumar, S.; Orvalho, V.; Cosker, D.; Chen, Min and Benes, Bedrich
    Facial animation is a time‐consuming and cumbersome task that requires years of experience and/or a complex and expensive set‐up. This becomes an issue, especially when animating the multitude of secondary characters required, e.g. in films or video‐games. We address this problem with a novel technique that relies on motion graphs to represent a landmarked database. Separate graphs are created for different facial regions, allowing a reduced memory footprint compared to the original data. The common poses are identified using a Euclidean‐based similarity metric and merged into the same node. This process traditionally requires a manually chosen threshold, however, we simplify it by optimizing for the desired graph compression. Motion synthesis occurs by traversing the graph using Dijkstra's algorithm, and coherent noise is introduced by swapping some path nodes with their neighbours. Expression labels, extracted from the database, provide the control mechanism for animation. We present a way of creating facial animation with reduced input that automatically controls timing and pose detail. Our technique easily fits within video‐game and crowd animation contexts, allowing the characters to be more expressive with less effort. Furthermore, it provides a starting point for content creators aiming to bring more life into their characters.Facial animation is a time‐consuming and cumbersome task that requires years of experience and/or a complex and expensive set‐up. This becomes an issue, especially when animating the multitude of secondary characters required, e.g. in films or video‐games. We address this problem with a novel technique that relies on motion graphs to represent a landmarked database. Separate graphs are created for different facial regions, allowing a reduced memory footprint compared to the original data. This process traditionally requires a manually chosen threshold, however, we simplify it by optimizing for the desired graph compression. Motion synthesis occurs by traversing the graph, with coherent noise introduced by varying the optimal path that connects the desired nodes. Expression labels, extracted from the database, provide an intuitive control mechanism for animation. Our technique easily fits within video‐game and crowd animation contexts, allowing the characters to be more expressive with less effort.
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    EUROGRAPHICS 2018: CGF 37-2 Frontmatter
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Gutierrez, Diego; Sheffer, Alla; Gutierrez, Diego; Sheffer, Alla
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    A Practical Approach to Physically-Based Reproduction of Diffusive Cosmetics
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Kim, Goanghun; Ko, Hyeong-Seok; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    In this paper, we introduce so-called the bSX method as a new way to utilize the Kubelka-Munk (K-M) model. Assuming the material is completely diffusive, the K-M model gives the reflectance and transmittance of the material from the observation of the material applied on a backing, where the observation includes the thickness of the material application. By rearranging the original K-M equation, we propose that the reflectance and transmittance can be calculated without knowing the thickness. This is a practically useful contribution. Based on the above finding, we develop the bSX method which can (1) capture the material specific parameters from the two photos - taken before and after the material application, and (2) reproduce its effect on a novel backing. We experimented the proposed method in various cases related to virtual cosmetic try-on, which include (1) capture from a single color backing, (2) capture from human skin backing, (3) reproduction of varying thickness effect, (4) reproduction of multi-layer cosmetic application effect, (5) applying the proposed method to makeup transfer. Compared to previous image-based makeup transfer methods, the bSX method reproduces the feel of the cosmetics more accurately.
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    Principal Geodesic Analysis in the Space of Discrete Shells
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Heeren, Behrend; Zhang, Chao; Rumpf, Martin; Smith, William; Ju, Tao and Vaxman, Amir
    Important sources of shape variability, such as articulated motion of body models or soft tissue dynamics, are highly nonlinear and are usually superposed on top of rigid body motion which must be factored out. We propose a novel, nonlinear, rigid body motion invariant Principal Geodesic Analysis (PGA) that allows us to analyse this variability, compress large variations based on statistical shape analysis and fit a model to measurements. For given input shape data sets we show how to compute a low dimensional approximating submanifold on the space of discrete shells, making our approach a hybrid between a physical and statistical model. General discrete shells can be projected onto the submanifold and sparsely represented by a small set of coefficients. We demonstrate two specific applications: model-constrained mesh editing and reconstruction of a dense animated mesh from sparse motion capture markers using the statistical knowledge as a prior.
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    Subdivision Schemes With Optimal Bounded Curvature Near Extraordinary Vertices
    (The Eurographics Association and John Wiley & Sons Ltd., 2018) Ma, Yue; Ma, Weiyin; Fu, Hongbo and Ghosh, Abhijeet and Kopf, Johannes
    We present a novel method to construct subdivision stencils near extraordinary vertices with limit surfaces having optimal bounded curvature at extraordinary positions. With the proposed method, subdivision stencils for newly inserted and updated vertices near extraordinary vertices are first constructed to ensure subdivision with G1 continuity and bounded curvature at extraordinary positions. The remaining degrees of freedom of the constructed subdivision stencils are further used to optimize the eigenbasis functions corresponding to the subsubdominant eigenvalues of the subdivision with respect to G2 continuity constraints. We demonstrate the method by replacing subdivision stencils near extraordinary vertices for Catmull-Clark subdivision and compare the results with the original Catmull-Clark subdivision and previous tuning schemes known with small curvature variation near extraordinary positions. The results show that the proposed method produces subdivision schemes with better or comparable curvature behavior around extraordinary vertices with comparatively simple subdivision stencils.