While discrete (metric) connections have become a staple of n -vector field design and analysis on simplicial meshes, the notion of torsion of a discrete connection has remained unstudied. This is all the more surprising as torsion is a crucial component in the fundamental theorem of Riemannian geometry, which introduces the existence and uniqueness of the Levi-Civita connection induced by the metric. In this paper, we extend the existing geometry processing toolbox by providing torsion control over discrete connections. Our approach consists in first introducing a new discrete Levi-Civita connection for a metric with locally-constant curvature to replace the hinge connection of a triangle mesh whose curvature is concentrated at singularities; from this reference connection, we define the discrete torsion of a connection to be the discrete dual 1-form by which a connection deviates from our discrete Levi-Civita connection. We discuss how the curvature and torsion of a discrete connection can then be controlled and assigned in a manner consistent with the continuous case. We also illustrate our approach through theoretical analysis and practical examples arising in vector and frame design.

-orthogonality and the accurate cohomology.

Locating neck-like features, or locally narrow parts, of a surface is crucial in various applications such as segmentation, shape analysis, path planning, and robotics. Topological methods are often utilized to find the set of shortest loops around handles and tunnels. However, there are abundant neck-like features on genus-0 shapes without any handles. While 3D geometry-aware topological approaches exist to find neck loops, their construction can be cumbersome and may even lead to geometrically wide loops. Thus we propose a "topology-aware geometric approach" to compute the tightest loops around neck features on surfaces, including genus-0 surfaces. Our algorithm starts with a volumetric representation of an input surface and then calculates the distance function of mesh points to the boundary surface as a Morse function. All neck features induce critical points of this Morse function where the Hessian matrix has precisely one positive eigenvalue, i.e., type-2 saddles. As we focus on geometric neck features, we bypass a topological construction such as the Morse-Smale complex or a lower-star filtration. Instead, we directly create a cutting plane through each neck feature. Each resulting loop can then be tightened to form a closed geodesic representation of the neck feature. Moreover, we offer criteria to measure the significance of a neck feature through the evolution of critical points when smoothing the distance function. Furthermore, we speed up the detection process through mesh simplification without compromising the quality of the output loops.

Controlling the size and shear of elements is crucial in pure hex or hex-dominant meshing. To this end, non-orthonormal frame fields that are almost everywhere integrable (except for the singularities) can play a key role. However, it is often challenging or impossible to generate such a frame field under the tight control of a general Riemannian metric field. Therefore, we propose to solve a relatively weaker problem, i.e., generating such a frame field for a Riemannian metric field that is flat away from singularities. Such a metric field admits a local isometry to 3D Euclidean space. Applying Cartans first structural equation to the associated rotation field, i.e., the rotation part of the frame field, we show that the rotation field must have zero covariant derivatives under the 3D connection induced by the metric field. This observation leads to a metric-aware smoothness measure, equivalent to local integrability. The use of such a measure can be justified on meshes associated with locally flat metric fields. We also propose a method to generate smooth metric fields under a few intuitive constraints. On cuboid shapes, our method generates singularities aware of the metric fields, which makes the parameterization match the input metric fields better than the conventional methods. For generic shapes, while our method generates visually similar results to those using boundary frame fields to guide the metric field generation, the integrability and consistency of the metric fields are still improved, as reflected by the statistics.

Most face relighting methods are able to handle diffuse shadows, but struggle to handle hard shadows, such as those cast by the nose. Methods that propose techniques for handling hard shadows often do not produce geometrically consistent shadows since they do not directly leverage the estimated face geometry while synthesizing them. We propose a novel differentiable algorithm for synthesizing hard shadows based on ray tracing, which we incorporate into training our face relighting model. Our proposed algorithm directly utilizes the estimated face geometry to synthesize geometrically consistent hard shadows. We demonstrate through quantitative and qualitative experiments on Multi-PIE and FFHQ that our method produces more geometrically consistent shadows than previous face relighting methods while also achieving state-of-the-art face relighting performance under directional lighting. In addition, we demonstrate that our differentiable hard shadow modeling improves the quality of the estimated face geometry over diffuse shading models.

Existing face relighting methods often struggle with two problems: maintaining the local facial details of the subject and accurately removing and synthesizing shadows in the relit image, especially hard shadows. We propose a novel deep face relighting method that addresses both problems. Our method learns to predict the ratio (quotient) image between a source image and the target image with the desired lighting, allowing us to relight the image while maintaining the local facial details. During training, our model also learns to accurately modify shadows by using estimated shadow masks to emphasize on the high-contrast shadow borders. Furthermore, we introduce a method to use the shadow mask to estimate the ambient light intensity in an image, and are thus able to leverage multiple datasets during training with different global lighting intensities. With quantitative and qualitative evaluations on the Multi-PIE and FFHQ datasets, we demonstrate that our proposed method faithfully maintains the local facial details of the subject and can accurately handle hard shadows while achieving state-of-the-art face relighting performance.

Singularity editing of a quadrangle mesh consists in shifting singularities around for either improving the quality of the mesh elements or canceling extraneous singularities, so as to increase mesh regularity. However, the particular structure of a quad mesh renders the exploration of allowable connectivity changes non-local and hard to automate. In this paper, we introduce a simple, principled, and general quad-mesh editing primitive with which pairs of arbitrarily distant singularities can be efficiently displaced around a mesh through a deterministic and reversible chain of local topological operations with a minimal footprint. Dubbed Q-zip as it acts as a zipper opening up and collapsing down quad strips, our practical mesh operator for singularity editing can be easily implemented via parallel transport of a reference compass between any two irregular vertices. Batches of Q-zips performed in parallel can then be used for efficient singularity editing.

A typical rainfall scenario contains tens of thousands of dynamic sound sources. A characteristic of the large-scale scene is the strong randomness in raindrop distribution, which makes it notoriously expensive to synthesize such sounds with purely physical methods. Moreover, the raindrops hitting different surfaces (liquid or various solids) can emit distinct sounds, for which prior methods with unified impact sound models are ill-suited. In this paper, we present a physically-based statistical simulation method to synthesize realistic rain sound, which respects surface materials. We first model the raindrop sound with two mechanisms, namely the initial impact and the subsequent pulsation of entrained bubbles. Then we generate material sound textures (MSTs) based on a specially designed signal decomposition and reconstruction model. This allows us to distinguish liquid surface with bubble sound and different solid surfaces with MSTs. Furthermore, we build a basic rain sound (BR-sound) bank with the proposed raindrop sound clustering method based on a statistical model, and design a sound source activator for simulating spatial propagation in an efficient manner. This novel method drastically decreases the computational cost while producing convincing sound results. Various experiments demonstrate the effectiveness of our sound simulation model.

We present a compendium of Hodge decompositions of vector fields on tetrahedral meshes embedded in the 3D Euclidean space. After describing the foundations of the Hodge decomposition in the continuous setting, we describe how to implement a five-component orthogonal decomposition that generically splits, for a variety of boundary conditions, any given discrete vector field expressed as discrete differential forms into two potential fields, as well as three additional harmonic components that arise from the topology or boundary of the domain. The resulting decomposition is proper and mimetic, in the sense that the theoretical dualities on the kernel spaces of vector Laplacians valid in the continuous case (including correspondences to cohomology and homology groups) are exactly preserved in the discrete realm. Such a decomposition only involves simple linear algebra with symmetric matrices, and can thus serve as a basic computational tool for vector field analysis in graphics, electromagnetics, fluid dynamics and elasticity.

Motivation: Protein pocket information is invaluable for drug target identification, agonist design, virtual screening and receptor-ligand binding analysis. A recent study indicates that about half holoproteins can simultaneously bind multiple interacting ligands in a large pocket containing structured sub-pockets. Although this hierarchical pocket and sub-pocket structure has a significant impact to multi-ligand synergistic interactions in the protein binding site, there is no method available for this analysis. This work introduces a computational tool based on differential geometry, algebraic topology and physics-based simulation to address this pressing issue. Results: We propose to detect protein pockets by evolving the convex hull surface inwards until it touches the protein surface everywhere. The governing partial differential equations (PDEs) include the mean curvature flow combined with the eikonal equation commonly used in the fast marching algorithm in the Eulerian representation. The surface evolution induced Morse function and Reeb graph are utilized to characterize the hierarchical pocket and sub-pocket structure in controllable detail. The proposed method is validated on PDBbind refined sets of 4414 protein-ligand complexes. Extensive numerical tests indicate that the proposed method not only provides a unique description of pocket-sub-pocket relations, but also offers efficient estimations of pocket surface area, pocket volume and pocket depth. Availability and implementation: Source code available at https://github.com/rdzhao/ProteinPocketDetection. Webserver available at http://weilab.math.msu.edu/PPD/.

We introduce an approach to quadrilateral meshing of arbitrary triangulated surfaces that combines the theoretical guarantees of Morse-based approaches with the practical advantages of parameterization methods. We first construct, through an eigensolver followed by a few Gauss-Newton iterations, a periodic four-dimensional vector field that aligns with a user-provided frame field and/or a set of features over the input mesh. A field-aligned parameterization is then greedily computed along a spanning tree based on the Dirichlet energy of the optimal periodic vector field, from which quad elements are efficiently extracted over most of the surface. The few regions not yet covered by elements are then upsampled and the first component of the periodic vector field is used as a Morse function to extract the remaining quadrangles. This hybrid parameterization- and Morse-based quad meshing method is not only fast (the parameterization is greedily constructed, and the Morse function only needs to be upsampled in the few uncovered patches), but is guaranteed to provide a feature-aligned quad mesh with non-degenerate cells that closely matches the input frame field over an arbitrary surface. We show that our approach is much faster than Morse-based techniques since it does not require a densely tessellated input mesh, and is significantly more robust than parameterization-based techniques on models with complex features.

We propose a novel approach to simulating the formation and evolution of stains on cloths in motion. We accurately capture the diffusion of a pigmented solution over a complex knitted or woven fabric through homogenization of its inhomogeneous and/or anisotropic properties into bulk anisotropic diffusion tensors. Secondary effects such as absorption, adsorption and evaporation are also accounted for through physically-based modeling. Finally, the influence of the cloth motion on the shape and evolution of the stain is captured by evaluating the inertial (e.g., centrifugal and Coriolis) forces experienced by the solution. The governing equations of motion are integrated in time directly on a deforming triangle mesh discretizing the inelastic cloth for efficiency and robustness. The deformation of the cloth can be precomputed or integrated through simplified two-way coupling, by using off-the-shell cloth simulations. Finally, numerical experiments demonstrate the plausibility of our results in practical applications by reproducing the usual shape and behavior of stains on various fabrics.

Abstract In this paper, we propose a controllable embedding method for high‐ and low‐dimensional geometry processing through sparse matrix eigenanalysis. Our approach is equally suitable to perform non‐linear dimensionality reduction on big data, or to offer non‐linear shape editing of 3D meshes and pointsets. At the core of our approach is the construction of a multi‐Laplacian quadratic form that is assembled from local operators whose kernels only contain locally‐affine functions. Minimizing this quadratic form provides an embedding that best preserves all relative coordinates of points within their local neighborhoods. We demonstrate the improvements that our approach brings over existing nonlinear dimensionality reduction methods on a number of datasets, and formulate the first eigen‐based as‐rigid‐as‐possible shape deformation technique by applying our affine‐kernel embedding approach to 3D data augmented with user‐imposed constraints on select vertices.

Given a photo collection of "unconstrained" face images of one individual captured under a variety of unknown pose, expression, and illumination conditions, this paper presents a method for reconstructing a 3D face surface model of the individual along with albedo information. Unlike prior work on face reconstruction that requires large photo collections, we formulate an approach to adapt to photo collections with a high diversity in both the number of images and the image quality. To achieve this, we incorporate prior knowledge about face shape by fitting a 3D morphable model to form a personalized template, following by using a novel photometric stereo formulation to complete the fine details, under a coarse-to-fine scheme. Our scheme incorporates a structural similarity-based local selection step to help identify a common expression for reconstruction while discarding occluded portions of faces. The evaluation of reconstruction performance is through a novel quality measure, in the absence of ground truth 3D scans. Superior large-scale experimental results are reported on synthetic, Internet, and personal photo collections.

Decorating the surfaces of 3D printed objects with color textures is still not readily available in most consumer-level or even high-end 3D printers. Existing techniques such as hydrographics color transfer suffer from the issues of air pockets in concave regions and discoloration in overly stretched regions. We propose a novel thermoforming-based coloring technique to alleviate these problems as well as to simplify the overall procedure. Thermoforming is a widely used technique in industry for plastic thin shell product manufacturing by pressing heated plastic sheets onto molds using atmospheric pressure. We attach on the transparent plastic sheet a precomputed color pattern decal prior to heating, and adhere it to 3D printed models treated as the molds in thermoforming. The 3D models are thus decorated with the desired color texture, as well as a thin, polished protective cover. The precomputation involves a physical simulation of the thermoforming process to compute the correct color pattern on the plastic sheet, and the vent hole layout on the 3D model for air pocket elimination. We demonstrate the effectiveness and accuracy of our computational model and our prototype thermoforming surface coloring system through physical experiments.

Given a collection of "in-the-wild" face images captured under a variety of unknown pose, expression, and illumination conditions, this paper presents a method for reconstructing a 3D face surface model of an individual along with albedo information. Motivated by the success of recent face reconstruction techniques on large photo collections, we extend prior work to adapt to low quality photo collections with fewer images. We achieve this by fitting a 3D Morphable Model to form a personalized template and developing a novel photometric stereo formulation, under a coarse-to-fine scheme. Superior experimental results are reported on synthetic and real-world photo collections.

This paper presents a variational method to generate cell complexes with local anisotropy conforming to the Hessian of any given convex function and for any given local mesh density. Our formulation builds upon approximation theory to offer an anisotropic extension of Centroidal Voronoi Tessellations which can be seen as a dual form of Optimal Delaunay Triangulation. We thus refer to the resulting anisotropic polytopal meshes as Optimal Voronoi Tessellations. Our approach sharply contrasts with previous anisotropic versions of Voronoi diagrams as it employs first-type Bregman diagrams, a generalization of power diagrams where sites are augmented with not only a scalar-valued weight but also a vector-valued shift. As such, our OVT meshes contain only convex cells with straight edges, and admit an embedded dual triangulation that is combinatorially-regular. We show the effectiveness of our technique using off-the-shelf computational geometry libraries.

We present a full geometric parameterization of generalized barycentric coordinates on convex polytopes. We show that these continuous and non-negative coefficients ensuring linear precision can be efficiently and exactly computed through a power diagram of the polytope's vertices and the evaluation point. In particular, we point out that well-known explicit coordinates such as Wachspress, Discrete Harmonic, Voronoi, or Mean Value correspond to simple choices of power weights. We also present examples of new barycentric coordinates, and discuss possible extensions such as power coordinates for non-convex polygons and smooth shapes.

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 L 2 -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.

This paper presents an algorithm for unconstrained 3D face reconstruction. The input to our algorithm is an “unconstrained” collection of face images captured under a diverse variation of poses, expressions, and illuminations, without meta data about cameras or timing. The output of our algorithm is a true 3D face surface model represented as a watertight triangulated surface with albedo data or texture information. 3D face reconstruction from a collection of unconstrained 2D images is a long-standing computer vision problem. Motivated by the success of the state-of-the-art method, we developed a novel photometric stereo-based method with two distinct novelties. First, working with a true 3D model allows us to enjoy the benefits of using images from all possible poses, including profiles. Second, by leveraging emerging face alignment techniques and our novel normal field-based Laplace editing, a combination of landmark constraints and photometric stereo-based normals drives our surface reconstruction. Given large photo collections and a ground truth 3D surface, we demonstrate the effectiveness and strength of our algorithm both qualitatively and quantitatively.

This paper presents a new technique for frame field generation. As generic frame fields (with arbitrary anisotropy, orientation, and sizing) can be regarded as cross fields in a specific Riemannian metric, we tackle frame field design by first computing a discrete metric on the input surface that is compatible with a sparse or dense set of input constraints. The final frame field is then found by computing an optimal cross field in this customized metric. We propose frame field design constraints on alignment, size, and skewness at arbitrary locations on the mesh as well as along feature curves, offering much improved flexibility over previous approaches. We demonstrate the advantages of our frame field generation through the automatic quadrangulation of man-made and organic shapes with controllable anisotropy, robust handling of narrow surface strips, and precise feature alignment. We also extend our technique to the design of n -vector fields.

We present a model-reduced variational Eulerian integrator for incompressible fluids, which combines the efficiency gains of dimension reduction, the qualitative robustness of coarse spatial and temporal resolutions of geometric integrators, and the simplicity of sub-grid accurate boundary conditions on regular grids to deal with arbitrarily-shaped domains. At the core of our contributions is a functional map approach to fluid simulation for which scalar- and vector-valued eigenfunctions of the Laplacian operator can be easily used as reduced bases. Using a variational integrator in time to preserve liveliness and a simple, yet accurate embedding of the fluid domain onto a Cartesian grid, our model-reduced fluid simulator can achieve realistic animations in significantly less computational time than full-scale non-dissipative methods but without the numerical viscosity from which current reduced methods suffer. We also demonstrate the versatility of our approach by showing how it easily extends to magnetohydrodynamics and turbulence modeling in 2D, 3D and curved domains.

We propose a real-time approach for indoor scene reconstruction. It is capable of producing a ready-to-use 3D geometric model even while the user is still scanning the environment with a consumer depth camera. Our approach features explicit representations of planar regions and nonplanar objects extracted from the noisy feed of the depth camera, via an online structure analysis on the dynamic, incomplete data. The structural information is incorporated into the volumetric representation of the scene, resulting in a seamless integration with KinectFusion's global data structure and an efficient implementation of the whole reconstruction process. Moreover, heuristics based on rectilinear shapes in typical indoor scenes effectively eliminate camera tracking drift and further improve reconstruction accuracy. The instantaneous feedback enabled by our on-the-fly structure analysis, including repeated object recognition, allows the user to selectively scan the scene and produce high-fidelity large-scale models efficiently. We demonstrate the capability of our system with real-life examples.

Abstract Geometry processing has made ample use of discrete representations of tangent vector fields and antisymmetric tensors (i.e., forms) on triangulations. Symmetric 2‐tensors, while crucial in the definition of inner products and elliptic operators, have received only limited attention. They are often discretized by first defining a coordinate system per vertex, edge or face, then storing their components in this frame field. In this paper, we introduce a representation of arbitrary 2‐tensor fields on triangle meshes. We leverage a coordinate‐free decomposition of continuous 2‐tensors in the plane to construct a finite‐dimensional encoding of tensor fields through scalar values on oriented simplices of a manifold triangulation. We also provide closed‐form expressions of pairing, inner product, and trace for this discrete representation of tensor fields, and formulate a discrete covariant derivative and a discrete Lie bracket. Our approach extends discrete/finite‐element exterior calculus, recovers familiar operators such as the weighted Laplacian operator, and defines discrete notions of divergence‐free, curl‐free, and traceless tensors–thus offering a numerical framework for discrete tensor calculus on triangulations. We finally demonstrate the robustness and accuracy of our operators on analytical examples, before applying them to the computation of anisotropic geodesic distances on discrete surfaces.

ABSTRACT While small‐scale fluid details are crucial elements for the creation of visually pleasing fluid animations, their synthesis often requires heavy computation with traditional grid‐based fluid simulation methods. This paper proposes a novel method for enhancing the appearance of small‐scale details through frequency‐domain analysis. Different from previous work, our method detects and improves fluid details in the frequency‐domain via lifting wavelet decomposition. Based on a coarse‐to‐fine mechanism, the lifting wavelet composition first transforms the velocity in a fine grid into the frequency domain. Next, the velocity field is enhanced separately for different frequency bands. A novel velocity fusion method is developed for the enhancement of low‐frequency parts. On the other hand, high‐frequency parts are enhanced using a specially designed vorticity confinement method. Finally, the application of the inverse lifting wavelet transform determines the final velocity field with increased fine details. Our method can generate perceptually interesting fluid details, matching human visual perception theory. The results of various experiments validate the effectiveness and efficiency of our method. Copyright © 2014 John Wiley & Sons, Ltd.

Polycube maps of triangle meshes have proved useful in a wide range of applications, including texture mapping and hexahedral mesh generation. However, constructing either fully automatically or with limited user control a low-distortion polycube from a detailed surface remains challenging in practice. We propose a variational method for deforming an input triangle mesh into a polycube shape through minimization of the ℓ 1 -norm of the mesh normals, regularized via an as-rigid-as-possible volumetric distortion energy. Unlike previous work, our approach makes no assumption on the orientation, or on the presence of features in the input model. User-guided control over the resulting polycube map is also offered to increase design flexibility. We demonstrate the robustness, efficiency, and controllability of our method on a variety of examples, and explore applications in hexahedral remeshing and quadrangulation.

We present FaceWarehouse, a database of 3D facial expressions for visual computing applications. We use Kinect, an off-the-shelf RGBD camera, to capture 150 individuals aged 7-80 from various ethnic backgrounds. For each person, we captured the RGBD data of her different expressions, including the neutral expression and 19 other expressions such as mouth-opening, smile, kiss, etc. For every RGBD raw data record, a set of facial feature points on the color image such as eye corners, mouth contour, and the nose tip are automatically localized, and manually adjusted if better accuracy is required. We then deform a template facial mesh to fit the depth data as closely as possible while matching the feature points on the color image to their corresponding points on the mesh. Starting from these fitted face meshes, we construct a set of individual-specific expression blendshapes for each person. These meshes with consistent topology are assembled as a rank-3 tensor to build a bilinear face model with two attributes: identity and expression. Compared with previous 3D facial databases, for every person in our database, there is a much richer matching collection of expressions, enabling depiction of most human facial actions. We demonstrate the potential of FaceWarehouse for visual computing with four applications: facial image manipulation, face component transfer, real-time performance-based facial image animation, and facial animation retargeting from video to image.

We present an automatic hexahedralization tool, based on a systematic treatment that removes some of the singularities that would lead to degenerate volumetric parameterization. Such singularities could be abundant in automatically generated frame fields guiding the interior and boundary layouts of the hexahedra in an all hexahedral mesh. We first give the mathematical definitions of the inadmissible singularities prevalent in frame fields, including newly introduced surface singularity types. We then give a practical framework for adjusting singularity graphs by automatically modifying the rotational transition of frames between charts (cells of a tetrahedral mesh for the volume) to resolve the issues detected in the internal and boundary singularity graph. After applying an additional re-smoothing of the frame field with the modified transition conditions, we cut the volume into a topologically trivial domain, with the original topology encoded by the self-intersections of the boundary of the domain, and solve a mixed integer problem on this domain for a global parameterization. Finally, a properly connected hexahedral mesh is constructed from the integer isosurfaces of (u,v,w) in the parameterization. We demonstrate the applicability of the method on complex shapes, and discuss its limitations.

Abstract Widely used for morphing between objects with arbitrary topology, distance field interpolation (DFI) handles topological transition naturally without the need for correspondence or remeshing, unlike surface‐based interpolation approaches. However, lack of correspondence in DFI also leads to ineffective control over the morphing process. In particular, unless the user specifies a dense set of landmarks, it is not even possible to measure the distortion of intermediate shapes during interpolation, let alone control it. To remedy such issues, we introduce an approach for establishing correspondence between the interior of two arbitrary objects, formulated as an optimal mass transport problem with a sparse set of landmarks. This correspondence enables us to compute non‐rigid warping functions that better align the source and target objects as well as to incorporate local rigidity constraints to perform as‐rigid‐aspossible DFI. We demonstrate how our approach helps achieve flexible morphing results with a small number of landmarks.

Animation techniques for controlling liquid simulation are challenging: they commonly require carefully setting initial and boundary conditions or performing a costly numerical optimization scheme against user-provided keyframes or animation sequences. Either way, the whole process is laborious and computationally expensive. We introduce a novel method to provide intuitive and interactive control of liquid simulation. Our method enables a user to locally edit selected keyframes and automatically propagates the editing in a nearby temporal region using geometric deformation. We formulate our local editing techniques as a small-scale nonlinear optimization problem which can be solved interactively. With this uniformed formulation, we propose three editing metaphors, including (i) sketching local fluid features using a few user strokes, (ii) dragging a local fluid region, and (iii) controlling a local shape with a small mesh patch. Finally, we use the edited liquid animation to guide an offline high-resolution simulation to recover more surface details. We demonstrate the intuitiveness and efficacy of our method in various practical scenarios.

We present a method for computing "choking" loops--a set of surface loops that describe the narrowing of the volumes inside/outside of the surface and extend the notion of surface homology and homotopy loops. The intuition behind their definition is that a choking loop represents the region where an offset of the original surface would get pinched. Our generalized loops naturally include the usual 2g handles/tunnels computed based on the topology of the genus-g surface, but also include loops that identify chokepoints or bottlenecks, i.e., boundaries of small membranes separating the inside or outside volume of the surface into disconnected regions. Our definition is based on persistent homology theory, which gives a measure to topological structures, thus providing resilience to noise and a well-defined way to determine topological feature size. More precisely, the persistence computed here is based on the lower star filtration of the interior or exterior 3D domain with the distance field to the surface being the associated 3D Morse function.

We present TransCut, a technique for interactive rendering of translucent objects undergoing fracturing and cutting operations. As the object is fractured or cut open, the user can directly examine and intuitively understand the complex translucent interior, as well as edit material properties through painting on cross sections and recombining the broken pieces—all with immediate and realistic visual feedback. This new mode of interaction with translucent volumes is made possible with two technical contributions. The first is a novel solver for the diffusion equation (DE) over a tetrahedral mesh that produces high-quality results comparable to the state-of-art finite element method (FEM) of Arbree et al. but at substantially higher speeds. This accuracy and efficiency is obtained by computing the discrete divergences of the diffusion equation and constructing the DE matrix using analytic formulas derived for linear finite elements. The second contribution is a multiresolution algorithm to significantly accelerate our DE solver while adapting to the frequent changes in topological structure of dynamic objects. The entire multiresolution DE solver is highly parallel and easily implemented on the GPU. We believe TransCut provides a novel visual effect for heterogeneous translucent objects undergoing fracturing and cutting operations.

Abstract In fluid animation, wake is one of the most important phenomena usually seen when an object is moving relative to the flow. However, in current shallow water simulation for interactive applications, this effect is greatly smeared out. In this paper, we present a method to efficiently synthesize these wakes. We adopt a generalized SPH method for shallow water simulation and two way solid fluid coupling. In addition, a 2D discrete vortex method is used to capture the detailed wake motions behind an obstacle, enriching the motion of SWE simulation. Our method is highly efficient since only 2D simulation is required. Moreover, by using a physically inspired procedural approach for particle seeding, DVM particles are only created in the wake region. Therefore, very few particles are required while still generating realistic wake patterns. When coupled with SWE, we show that these patterns can be seen using our method with marginal overhead.

A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.

In this paper, we present a method for constructing a 3D cross-frame field , a 3D extension of the 2D cross-frame field as applied to surfaces in applications such as quadrangulation and texture synthesis. In contrast to the surface cross-frame field (equivalent to a 4-Way Rotational-Symmetry vector field), symmetry for 3D cross-frame fields cannot be formulated by simple one-parameter 2D rotations in the tangent planes. To address this critical issue, we represent the 3D frames by spherical harmonics, in a manner invariant to combinations of rotations around any axis by multiples of π/2. With such a representation, we can formulate an efficient smoothness measure of the cross-frame field. Through minimization of this measure under certain boundary conditions, we can construct a smooth 3D cross-frame field that is aligned with the surface normal at the boundary. We visualize the resulting cross-frame field through restrictions to the boundary surface, streamline tracing in the volume, and singularities. We also demonstrate the application of the 3D cross-frame field to producing hexahedron-dominant meshes for given volumes, and discuss its potential in high-quality hexahedralization, much as its 2D counterpart has shown in quadrangulation.

In this paper, we introduce an interactive approach to generate physically based shape interpolation between poses. We extend linear modal analysis to offer an efficient and robust numerical technique to generate physically-plausible dynamics even for very large deformation. Our method also provides a rich set of intuitive editing tools with real-time feedback, including control over vibration frequencies, amplitudes, and damping of the resulting interpolation sequence. We demonstrate the versatility of our approach through a series of complex dynamic shape interpolations.

Abstract We present a simple and effective algorithm to transfer deformation between surface meshes with multiple components. The algorithm automatically computes spatial relationships between components of the target object, builds correspondences between source and target, and finally transfers deformation of the source onto the target while preserving cohesion between the target's components. We demonstrate the versatility of our approach on various complex models.

One of the challenges in automatic face recognition is to achieve temporal invariance. In other words, the goal is to come up with a representation and matching scheme that is robust to changes due to facial aging. Facial aging is a complex process that affects both the 3D shape of the face and its texture (e.g., wrinkles). These shape and texture changes degrade the performance of automatic face recognition systems. However, facial aging has not received substantial attention compared to other facial variations due to pose, lighting, and expression. We propose a 3D aging modeling technique and show how it can be used to compensate for the age variations to improve the face recognition performance. The aging modeling technique adapts view-invariant 3D face models to the given 2D face aging database. The proposed approach is evaluated on three different databases (i.g., FG-NET, MORPH, and BROWNS) using FaceVACS, a state-of-the-art commercial face recognition engine.

Numerical viscosity has long been a problem in fluid animation. Existing methods suffer from intrinsic artificial dissipation and often apply complicated computational mechanisms to combat such effects. Consequently, dissipative behavior cannot be controlled or modeled explicitly in a manner independent of time step size, complicating the use of coarse previews and adaptive-time stepping methods. This paper proposes simple, unconditionally stable, fully Eulerian integration schemes with no numerical viscosity that are capable of maintaining the liveliness of fluid motion without recourse to corrective devices. Pressure and fluxes are solved efficiently and simultaneously in a time-reversible manner on simplicial grids, and the energy is preserved exactly over long time scales in the case of inviscid fluids. These integrators can be viewed as an extension of the classical energy-preserving Harlow-Welch / Crank-Nicolson scheme to simplicial grids.

The variation caused by aging has not received adequate attention compared with pose, lighting, and expression variations. Aging is a complex process that affects both the 3D shape of the face and its texture (e.g., wrinkles). While the facial age modeling has been widely studied in computer graphics community, only a few studies have been reported in computer vision literature on age-invariant face recognition. We propose an automatic aging simulation technique that can assist any existing face recognition engine for aging-invariant face recognition. We learn the aging patterns of shape and the corresponding texture in 3D domain by adapting a 3D morphable model to the 2D aging database (public domain FG-NET). At recognition time, each probe and all gallery images are modified to compensate for the age-induced variation using an intermediate 3D model deformation and a texture modification, prior to matching. The proposed approach is evaluated on a set of age-separated probe and gallery data using a state-of-the-art commercial face recognition engine, FaceVACS. Use of 3D aging model improves the rank-1 matching accuracy on FG-NET database from 28.0% to 37.8%, on average.

Abstract We present a spectral approach to automatically and efficiently obtain discrete free‐boundary conformal parameterizations of triangle mesh patches, without the common artifacts due to positional constraints on vertices and without undue bias introduced by sampling irregularity. High‐quality parameterizations are computed through a constrained minimization of a discrete weighted conformal energy by finding the largest eigenvalue/eigenvector of a generalized eigenvalue problem involving sparse, symmetric matrices. We demonstrate that this novel and robust approach improves on previous linear techniques both quantitatively and qualitatively.

In this paper we present an approach to enrich skeleton-driven animations with physically-based secondary deformation in real time. To achieve this goal, we propose a novel, surface-based deformable model that can interactively emulate the dynamics of both low-and high-frequency volumetric effects. Given a surface mesh and a few sample sequences of its physical behavior, a set of motion parameters of the material are learned during an off-line preprocessing step. The deformable model is then applicable to any given skeleton-driven animation of the surface mesh. Additionally, our dynamic skinning technique can be entirely implemented on GPUs and executed with great efficiency. Thus, with minimal changes to the conventional graphics pipeline, our approach can drastically enhance the visual experience of skeleton-driven animations by adding secondary deformation in real time.

A shell map (Porumbescu et al., 2005) is a bijective mapping between shell space (the space between a base surface and its offset) and texture space. It can be used to generate small-scale features on surfaces using a variety of modeling techniques. In this paper, we present an efficient algorithm, which reduces distortion by construction, for the offset surface generation of triangular meshes. The basic idea is to independently offset each triangle of the base mesh, and then stitch them up by solving a Poisson equation. We then introduce the details for computation of a stretch metric, which measures the distortion of shell maps. Our results show a substantial improvement compared to previous results

Visual quality, low computational cost, and numerical stability are foremost goals in computer animation. An important ingredient in achieving these goals is the conservation of fundamental motion invariants. For example, rigid and deformable body simulation benefits greatly from the conservation of linear and angular momenta. In the case of fluids, however, none of the current techniques focuses on conserving invariants, and consequently, often introduce a visually disturbing numerical diffusion of vorticity . Just as important visually is the resolution of complex simulation domains. Doing so with regular (even if adaptive) grid techniques can be computationally delicate. In this article, we propose a novel technique for the simulation of fluid flows. It is designed to respect the defining differential properties, that is, the conservation of circulation along arbitrary loops as they are transported by the flow. Consequently, our method offers several new and desirable properties: Arbitrary simplicial meshes (triangles in 2D, tetrahedra in 3D) can be used to define the fluid domain; the computations involved in the update procedure are efficient due to discrete operators with small support; and it preserves discrete circulation , avoiding numerical diffusion of vorticity.

We present a purely Eulerian framework for geometry processing of surfaces and foliations. Contrary to current Eulerian methods used in graphics, we use conservative methods and a variational interpretation, offering a unified framework for routine surface operations such as smoothing, offsetting, and animation. Computations are performed on a fixed volumetric grid without recourse to Lagrangian techniques such as triangle meshes, particles, or path tracing. At the core of our approach is the use of the Coarea Formula to express area integrals over isosurfaces as volume integrals. This enables the simultaneous processing of multiple isosurfaces, while a single interface can be treated as the special case of a dense foliation. We show that our method is a powerful alternative to conventional geometric representations in delicate cases such as the handling of high-genus surfaces, weighted offsetting, foliation smoothing of medical datasets, and incompressible fluid animation.

We present mesh puppetry , a variational framework for detail-preserving mesh manipulation through a set of high-level, intuitive, and interactive design tools. Our approach builds upon traditional rigging by optimizing skeleton position and vertex weights in an integrated manner. New poses and animations are created by specifying a few desired constraints on vertex positions, balance of the character, length and rigidity preservation, joint limits, and/or self-collision avoidance. Our algorithm then adjusts the skeleton and solves for the deformed mesh simultaneously through a novel cascading optimization procedure, allowing realtime manipulation of meshes with 50 K + vertices for fast design of pleasing and realistic poses. We demonstrate the potential of our framework through an interactive deformation platform and various applications such as deformation transfer and motion retargeting.

We introduce a framework for quadrangle meshing of discrete manifolds. Based on discrete differential forms, our method hinges on extending the discrete Laplacian operator (used extensively in modeling and animation) to allow for line singularities and singularities with fractional indices. When assembled into a singularity graph, these line singularities are shown to considerably increase the design flexibility of quad meshing. In particular, control over edge alignments and mesh sizing are unique features of our novel approach. Another appeal of our method is its robustness and scalability from a numerical viewpoint: we simply solve a sparse linear system to generate a pair of piecewise-smooth scalar fields whose isocontours form a pure quadrangle tiling, with no T-junctions.

Vertex- and face-based subdivision schemes are now routinely used in geometric modeling and computational science, and their primal/dual relationships are well studied. In this paper, we interpret these schemes as defining bases for discrete differential 0- resp. 2-forms , and complete the picture by introducing edge-based subdivision schemes to construct the missing bases for discrete differential 1-forms. Such subdivision schemes map scalar coefficients on edges from the coarse to the refined mesh and are intrinsic to the surface. Our construction is based on treating vertex-, edge-, and face-based subdivision schemes as a joint triple and enforcing that subdivision commutes with the topological exterior derivative. We demonstrate our construction for the case of arbitrary topology triangle meshes. Using Loop's scheme for 0-forms and generalized half-box splines for 2-forms results in a unique generalized spline scheme for 1-forms, easily incorporated into standard subdivision surface codes. We also provide corresponding boundary stencils. Once a metric is supplied, the scalar 1-form coefficients define a smooth tangent vector field on the underlying subdivision surface. Design of tangent vector fields is made particularly easy with this machinery as we demonstrate.

We introduce mesh quilting , a geometric texture synthesis algorithm in which a 3D texture sample given in the form of a triangle mesh is seamlessly applied inside a thin shell around an arbitrary surface through local stitching and deformation. We show that such geometric textures allow interactive and versatile editing and animation, producing compelling visual effects that are difficult to achieve with traditional texturing methods. Unlike pixel-based image quilting, mesh quilting is based on stitching together 3D geometry elements. Our quilting algorithm finds corresponding geometry elements in adjacent texture patches, aligns elements through local deformation, and merges elements to seamlessly connect texture patches. For mesh quilting on curved surfaces, a critical issue is to reduce distortion of geometry elements inside the 3D space of the thin shell. To address this problem we introduce a low-distortion parameterization of the shell space so that geometry elements can be synthesized even on very curved objects without the visual distortion present in previous approaches. We demonstrate how mesh quilting can be used to generate convincing decorations for a wide range of geometric textures.

We propose a technique, called TextureMontage , to seamlessly map a patchwork of texture images onto an arbitrary 3D model. A texture atlas can be created through the specification of a set of correspondences between the model and any number of texture images. First, our technique automatically partitions the mesh and the images, driven solely by the choice of feature correspondences. Most charts will then be parameterized over their corresponding image planes through the minimization of a distortion metric based on both geometric distortion and texture mismatch across patch boundaries and images. Lastly, a surface texture inpainting technique is used to fill in the remaining charts of the surface with no corresponding texture patches. The resulting texture mapping satisfies the (sparse or dense) user-specified constraints while minimizing the distortion of the texture images and ensuring a smooth transition across the boundaries of different mesh patches. Seamless Texturing of Arbitrary Surfaces From Multiple Images

While 2D and 3D vector fields are ubiquitous in computational sciences, their use in graphics is often limited to regular grids, where computations are easily handled through finite-difference methods. In this paper, we propose a set of simple and accurate tools for the analysis of 3D discrete vector fields on arbitrary tetrahedral grids. We introduce a variational, multiscale decomposition of vector fields into three intuitive components: a divergence-free part, a curl-free part, and a harmonic part. We show how our discrete approach matches its well-known smooth analog, called the Helmotz-Hodge decomposition, and that the resulting computational tools have very intuitive geometric interpretation. We demonstrate the versatility of these tools in a series of applications, ranging from data visualization to fluid and deformable object simulation.