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Item A Parallel Approach to Compression and Decompression of Triangle Meshes using the GPU(The Eurographics Association and John Wiley & Sons Ltd., 2017) Jakob, Johannes; Buchenau, Christoph; Guthe, Michael; Bærentzen, Jakob Andreas and Hildebrandt, KlausMost state-of-the-art compression algorithms use complex connectivity traversal and prediction schemes, which are not efficient enough for online compression of large meshes. In this paper we propose a scalable massively parallel approach for compression and decompression of large triangle meshes using the GPU. Our method traverses the input mesh in a parallel breadth-first manner and encodes the connectivity data similarly to the well known cut-border machine. Geometry data is compressed using a local prediction strategy. In contrast to the original cut-border machine, we can additionally handle triangle meshes with inconsistently oriented faces. Our approach is more than one order of magnitude faster than currently used methods and achieves competitive compression rates.Item Patch-Collaborative Spectral Point-Cloud Denoising(The Eurographics Association and Blackwell Publishing Ltd., 2013) Rosman, G.; Dubrovina, A.; Kimmel, R.; Holly Rushmeier and Oliver DeussenWe present a new framework for point cloud denoising by patch-collaborative spectral analysis. A collaborative generalization of each surface patch is defined, combining similar patches from the denoised surface. The Laplace–Beltrami operator of the collaborative patch is then used to selectively smooth the surface in a robust manner that can gracefully handle high levels of noise, yet preserves sharp surface features. The resulting denoising algorithm competes favourably with state‐of‐the‐art approaches, and extends patch‐based algorithms from the image processing domain to point clouds of arbitrary sampling. We demonstrate the accuracy and noise‐robustness of the proposed algorithm on standard benchmark models as well as range scans, and compare it to existing methods for point cloud denoising.We present a new framework for point cloud denoising by patch‐collaborative spectral analysis. A collaborative generalization of each surface patch is defined, combining similar patches from the denoised surface. The Laplace‐Beltrami operator of the collaborative patch is then used to selectively smooth the surface in a robust manner that can gracefully handle high levels of noise, yet preserves sharp surface features.Item Vega: Non-Linear FEM Deformable Object Simulator(The Eurographics Association and Blackwell Publishing Ltd., 2013) Sin, F. S.; Schroeder, D.; Barbic, J.; Holly Rushmeier and Oliver DeussenThis practice and experience paper describes a robust C++ implementation of several non-linear solid three-dimensional deformable object strategies commonly employed in computer graphics, named the Vega finite element method (FEM) simulation library. Deformable models supported include co-rotational linear FEM elasticity, Saint-Venant Kirchhoff FEM model, mass-spring system and invertible FEM models: neo-Hookean, Saint-Venant Kirchhoff and Mooney-Rivlin. We provide several timestepping schemes, including implicit Newmark and backward Euler integrators, and explicit central differences. The implementation of material models is separated from integration, which makes it possible to employ our code not only for simulation, but also for deformable object control and shape modelling. We extensively compare the different material models and timestepping schemes. We provide practical experience and insight gained while using our code in several computer animation and simulation research projects.This practice and experience paper describes a robust C++ implementation of several nonlinear solid 3D deformable object strategies commonly employed in computer graphics, named the Vega FEM simulation library. Deformable models supported include co-rotational linear FEM elasticity, Saint-Venant Kirchhoff FEM model, mass-spring system, and invertible FEM models: neo-Hookean, Saint-Venant Kirchhoff, and Mooney-Rivlin. We provide several timestepping schemes, including implicit Newmark and backward Euler integrators, and explicit central differences. The implementation of material models is separated from integration, which makes it possible to employ our code not only for simulation, but also for deformable object control and shape modeling. We extensively compare the different material models and timestepping schemes. We provide practical experience and insight gained while using our code in several computer animation and simulation research projects.Item Polycube Simplification for Coarse Layouts of Surfaces and Volumes(The Eurographics Association and John Wiley & Sons Ltd., 2016) Cherchi, Gianmarco; Livesu, Marco; Scateni, Riccardo; Maks Ovsjanikov and Daniele PanozzoRepresenting digital objects with structured meshes that embed a coarse block decomposition is a relevant problem in applications like computer animation, physically-based simulation and Computer Aided Design (CAD). One of the key ingredients to produce coarse block structures is to achieve a good alignment between the mesh singularities (i.e., the corners of each block). In this paper we improve on the polycube-based meshing pipeline to produce both surface and volumetric coarse block-structured meshes of general shapes. To this aim we add a new step in the pipeline. Our goal is to optimize the positions of the polycube corners to produce as coarse as possible base complexes. We rely on re-mapping the positions of the corners on an integer grid and then using integer numerical programming to reach the optimal. To the best of our knowledge this is the first attempt to solve the singularity misalignment problem directly in polycube space. Previous methods for polycube generation did not specifically address this issue. Our corner optimization strategy is efficient and requires a negligible extra running time for the meshing pipeline. In the paper we show that our optimized polycubes produce coarser block structured surface and volumetric meshes if compared with previous approaches. They also induce higher quality hexahedral meshes and are better suited for spline fitting because they reduce the number of splines necessary to cover the domain, thus improving both the efficiency and the overall level of smoothness throughout the volume.Item Sparse Iterative Closest Point(The Eurographics Association and Blackwell Publishing Ltd., 2013) Bouaziz, Sofien; Tagliasacchi, Andrea; Pauly, Mark; Yaron Lipman and Hao ZhangRigid registration of two geometric data sets is essential in many applications, including robot navigation, surface reconstruction, and shape matching. Most commonly, variants of the Iterative Closest Point (ICP) algorithm are employed for this task. These methods alternate between closest point computations to establish correspondences between two data sets, and solving for the optimal transformation that brings these correspondences into alignment. A major difficulty for this approach is the sensitivity to outliers and missing data often observed in 3D scans. Most practical implementations of the ICP algorithm address this issue with a number of heuristics to prune or reweight correspondences. However, these heuristics can be unreliable and difficult to tune, which often requires substantial manual assistance. We propose a new formulation of the ICP algorithm that avoids these difficulties by formulating the registration optimization using sparsity inducing norms. Our new algorithm retains the simple structure of the ICP algorithm, while achieving superior registration results when dealing with outliers and incomplete data. The complete source code of our implementation is provided at http://lgg.epfl.ch/sparseicp.Item Rib-reinforced Shell Structure(The Eurographics Association and John Wiley & Sons Ltd., 2016) Li, Wei; Zheng, Anzong; You, Lihua; Yang, Xiaosong; Zhang, Jianjun; Liu, Ligang; Jernej Barbic and Wen-Chieh Lin and Olga Sorkine-HornungShell structures are extensively used in engineering due to their efficient load-carrying capacity relative to material volume. However, large-span shells require additional supporting structures to strengthen fragile regions. The problem of designing optimal stiffeners is therefore becoming a major challenge for shell applications. To address it, we propose a computational framework to design and optimize rib layout on arbitrary shell to improve the overall structural stiffness and mechanical performance. The essential of our method is to place ribs along the principal stress lines which reflect paths of material continuity and indicates trajectories of internal forces. Given a surface and user-specified external loads, we perform a Finite Element Analysis. Using the resulting principal stress field, we generate a quad-mesh whose edges align with this cross field. Then we extract an initial rib network from the quad-mesh. After simplifying rib network by removing ribs with little contribution, we perform a rib flow optimization which allows ribs to swing on surface to further adjust rib distribution. Finally, we optimize rib cross-section to maximally reduce material usage while achieving certain structural stiffness requirements. We demonstrate that our rib-reinforced shell structures achieve good static performances. And experimental results by 3D printed objects show the effectiveness of our method.Item Advection-Based Function Matching on Surfaces(The Eurographics Association and John Wiley & Sons Ltd., 2016) Azencot, Omri; Vantzos, Orestis; Ben-Chen, Mirela; Maks Ovsjanikov and Daniele PanozzoA tangent vector field on a surface is the generator of a smooth family of maps from the surface to itself, known as the flow. Given a scalar function on the surface, it can be transported, or advected, by composing it with a vector field's flow. Such transport is exhibited by many physical phenomena, e.g., in fluid dynamics. In this paper, we are interested in the inverse problem: given source and target functions, compute a vector field whose flow advects the source to the target. We propose a method for addressing this problem, by minimizing an energy given by the advection constraint together with a regularizing term for the vector field. Our approach is inspired by a similar method in computational anatomy, known as LDDMM, yet leverages the recent framework of functional vector fields for discretizing the advection and the flow as operators on scalar functions. The latter allows us to efficiently generalize LDDMM to curved surfaces, without explicitly computing the flow lines of the vector field we are optimizing for. We show two approaches for the solution: using linear advection with multiple vector fields, and using non-linear advection with a single vector field. We additionally derive an approximated gradient of the corresponding energy, which is based on a novel vector field transport operator. Finally, we demonstrate applications of our machinery to intrinsic symmetry analysis, function interpolation and map improvement.Item Spatial Matching of Animated Meshes(The Eurographics Association and John Wiley & Sons Ltd., 2016) Seo, Hyewon; Cordier, Frederic; Eitan Grinspun and Bernd Bickel and Yoshinori DobashiThis paper presents a new technique which makes use of deformation and motion properties between animated meshes for finding their spatial correspondences. Given a pair of animated meshes exhibiting a semantically similar motion, we compute a sparse set of feature points on each mesh and compute spatial correspondences among them so that points with similar motion behavior are put in correspondence. At the core of our technique is our new, dynamic feature descriptor named AnimHOG, which encodes local deformation characteristics. AnimHOG is ob-tained by computing the gradient of a scalar field inside the spatiotemporal neighborhood of a point of interest, where the scalar values are obtained from the deformation characteristic associated with each vertex and at each frame. The final matching has been formulated as a discreet optimization problem that finds the matching of each feature point on the source mesh so that the descriptor similarity between the corresponding feature pairs as well as compatibility and consistency as measured across the pairs of correspondences are maximized. Consequently, reliable correspondences can be found even among the meshes of very different shape, as long as their motions are similar. We demonstrate the performance of our technique by showing the good quality of matching results we obtained on a number of animated mesh pairs.Item 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, AmirImportant 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.Item A Data-Driven Approach to Realistic Shape Morphing(The Eurographics Association and Blackwell Publishing Ltd., 2013) Gao, Lin; Lai, Yu-Kun; Huang, Qi-Xing; Hu, Shi-Min; I. Navazo, P. PoulinMorphing between 3D objects is a fundamental technique in computer graphics. Traditional methods of shape morphing focus on establishing meaningful correspondences and finding smooth interpolation between shapes. Such methods however only take geometric information as input and thus cannot in general avoid producing unnatural interpolation, in particular for large-scale deformations. This paper proposes a novel data-driven approach for shape morphing. Given a database with various models belonging to the same category, we treat them as data samples in the plausible deformation space. These models are then clustered to form local shape spaces of plausible deformations. We use a simple metric to reasonably represent the closeness between pairs of models. Given source and target models, the morphing problem is casted as a global optimization problem of finding a minimal distance path within the local shape spaces connecting these models. Under the guidance of intermediate models in the path, an extended as-rigid-as-possible interpolation is used to produce the final morphing. By exploiting the knowledge of plausible models, our approach produces realistic morphing for challenging cases as demonstrated by various examples in the paper.