Bézier curves are typically used for interactively designing polynomial curves, but it is well known that this becomes increasingly unintuitive as the degree of the curve grows. Gauss–Legendre (GL) curves have been proposed as an alternative for modelling high-degree polynomial curves. They come with the advantage of preserving a close relationship between the curve and its control polygon, but are costly to evaluate in their native form. We first show how to express GL curves in the Legendre basis. Building on this and taking advantage of the three-term recurrence relation of Legendre polynomials, we explore a linear-time algorithm for evaluating GL curves. We further introduce a more general family of GL- curves, with GL curves corresponding to the case and observe that GL- curves are often remarkably similar to cubic B-spline curves. Unlike Bézier curves, the start and the end of a GL- curve are not tangent to the first and the last edge of the control polygon, respectively, and we present a strategy for restoring this property.

Range functions are a fundamental tool for certified computations in geometric modelling, computer graphics, and robotics, but traditional range functions have only quadratic convergence order ( ). For “superior” convergence order (i.e., ), we exploit the Cornelius–Lohner framework in order to introduce new bivariate range functions based on Taylor, Lagrange, and Hermite interpolation. In particular, we focus on practical range functions with cubic and quartic convergence order. We implemented them in Julia and provide experimental validation of their performance in terms of efficiency and efficacy. • Classical bivariate range functions have only quadratic convergence order. • We derive bivariate range functions with cubic and quartic convergence order. • The theoretically proven convergence orders are validated by numerical examples.

We describe a simple and practical algorithm for compact routing on connected random unit disk graphs. Using a recursive nested dissection of an n -vertex graph based on compact and balanced vertex separators, we construct routing tables with an average of O (log 2 n ) entries per vertex in a preprocessing step. The routing tables then support handshaking-based routing, where the handshaking can be implemented similarly to a DNS lookup. Our routing algorithm is guaranteed to deliver on the graph, while incurring moderate stretch. We describe a basic version of the algorithm that requires modifiable headers and a more advanced version that eliminates this need and incurs less stretch.

Generalized barycentric coordinates provide a simple way of interpolating data given at the vertices of a polygon or polyhedron, with widespread applications in computer graphics, geometry processing, and other fields. Transfinite barycentric coordinates, also known as barycentric kernels, extend this idea to curved domains and can be used to interpolate continuous data given on the boundary of such domains. We present a novel framework for defining non-negative barycentric kernels over arbitrary bounded planar domains. This framework is inspired by the construction of a transfinite version of maximum likelihood coordinates and can be used to define a variety of barycentric kernels, including a simple pseudo-harmonic kernel and a non-negative variant of the mean value kernel. Moreover, we propose a novel barycentric kernel which yields transfinite interpolants that are similar to harmonic interpolants. We tested our new kernel for domains and boundary data described by closed uniform quadratic splines and in particular for image deformation. The results indicate that our method has several advantages over alternative approaches.

The generalization of barycentric coordinates to arbitrary simple polygons with more than three vertices has been a subject of study for a long time. Among the different constructions proposed, mean value coordinates have emerged as a popular choice, particularly due to their suitability for the non-convex setting. Since their introduction, they have found applications in numerous fields, and several equivalent formulas for their evaluation have been presented in the literature. However, so far, there has been no study regarding their numerical stability. In this paper, we aim to investigate the numerical stability of the algorithms that compute mean value coordinates. We show that all the known methods exhibit instability in some regions of the domain. To address this problem, we introduce a new formula for computing mean value coordinates, explain how to implement it, and formally prove that our new algorithm provides a stable evaluation of mean value coordinates. We validate our results through numerical experiments.

Subdivision schemes are used to generate smooth curves by iteratively refining an initial control polygon. The simplest such schemes are corner cutting schemes, which specify two distinct points on each edge of the current polygon and connect them to get the refined polygon, thus cutting off the corners of the current polygon. While de Boor (1987) shows that this process always converges to a Lipschitz continuous limit curve, no matter how the points on each edge are chosen, Gregory and Qu (1996) discover that the limit curve is continuously differentiable under certain constraints. We extend these results and show that the limit curve can even be curvature continuous for specific sequences of cut ratios. • Proof that non-uniform corner cutting schemes can generate curvature continuous limit curves. • Corner cutting rules for generating cubic B-splines as limit curves. • Corner cutting rules for generating cubic non-uniform γ -B-splines as limit curves. • Corner cutting rules for generating cubic non-uniform rational γ -B-splines as limit curves.

The aim of this work is to provide new characterizations of planar quintic Pythagorean-hodograph curves. The first two are algebraic and consist of two and three equations, respectively, in terms of the edges of the Bézier control polygon as complex numbers. These equations are symmetric with respect to the edge indices and cover curves with generic as well as degenerate control polygons. The last two characterizations are geometric and rely both on just two auxiliary points outside the control polygon. One requires two (possibly degenerate) quadrilaterals to be similar, and the other highlights two families of three similar triangles. All characterizations are a step forward with respect to the state of the art, and they can be linked to the well-established counterparts for planar cubic Pythagorean-hodograph curves. The key ingredient for proving the aforementioned results is a novel general expression for the hodograph of the curve.

Abstract Interactive deformation via control handles is essential in computer graphics for the modeling of 3D geometry. Deformation control structures include lattices for free‐form deformation and skeletons for character articulation, but this report focuses on cage‐based deformation. Cages for deformation control are coarse polygonal meshes that encase the to‐be‐deformed geometry, enabling high‐resolution deformation. Cage‐based deformation enables users to quickly manipulate 3D geometry by deforming the cage. Due to their utility, cage‐based deformation techniques increasingly appear in many geometry modeling applications. For this reason, the computer graphics community has invested a great deal of effort in the past decade and beyond into improving automatic cage generation and cage‐based deformation. Recent advances have significantly extended the practical capabilities of cage‐based deformation methods. As a result, there is a large body of research on cage‐based deformation. In this report, we provide a comprehensive overview of the current state of the art in cage‐based deformation of 3D geometry. We discuss current methods in terms of deformation quality, practicality, and precomputation demands. In addition, we highlight potential future research directions that overcome current issues and extend the set of practical applications. In conjunction with this survey, we publish an application to unify the most relevant deformation methods. Our report is intended for computer graphics researchers, developers of interactive geometry modeling applications, and 3D modeling and character animation artists.

We present a novel approach for generating isotropic surface triangle meshes directly from unoriented 3D point clouds, with the mesh density adapting to the estimated local feature size (LFS). Popular reconstruction pipelines first reconstruct a dense mesh from the input point cloud and then apply remeshing to obtain an isotropic mesh. The sequential pipeline makes it hard to find a lower-density mesh while preserving more details. Instead, our approach reconstructs both an implicit function and an LFS-aware mesh sizing function directly from the input point cloud, which is then used to produce the final LFS-aware mesh without remeshing. We combine local curvature radius and shape diameter to estimate the LFS directly from the input point clouds. Additionally, we propose a new mesh solver to solve an implicit function whose zero level set delineates the surface without requiring normal orientation. The added value of our approach is generating isotropic meshes directly from 3D point clouds with an LFS-aware density, thus achieving a trade-off between geometric detail and mesh complexity. Our experiments also demonstrate the robustness of our method to noise, outliers, and missing data and can preserve sharp features for CAD point clouds.

Barycentric rational interpolation is a recent interpolation method with several favourable properties. In this article, we present the BRI class, which features a new C++ class template that contains all variables and functions related to linear barycentric rational interpolation. While several methods exist to evaluate a barycentric rational interpolant, the class is designed to autonomously select the best method to use on a case-by-case basis, as it takes into account the latest results regarding the efficiency and numerical stability of barycentric rational interpolation [ 15 ]. Moreover, we describe a new technique that makes the code robust and less prone to overflow and underflow errors. In addition to the standard C++ data types, the BRI template variables can also be defined with arbitrary precision because the BRI class is compatible with the Multiple Precision Floating-Point Reliable (MPFR) library [ 14 ].

Bézier curves are an essential tool for curve design. Due to their properties, common operations such as translation, rotation, or scaling can be applied to the curve by simply modifying the control polygon of the curve. More flexibility, and thus more diverse types of curves, can be achieved by associating a weight with each control point, that is, by considering rational Bézier curves. As shown by Ramanantoanina and Hormann (2021), additional and more direct control over the curve shape can be achieved by exploiting the correspondence between the rational Bézier and the interpolating barycentric form and by exploring the effect of changing the degrees of freedom of the latter (interpolation points, weights, and nodes). In this paper, we explore similar editing possibilities for closed curves, in particular for the rational extension of the periodic Bézier curves that were introduced by Sánchez-Reyes (2009). We show how to convert back and forth between the periodic rational Bézier and the interpolating trigonometric barycentric form, derive a necessary condition to avoid poles of a trigonometric rational interpolant, and devise a general framework to perform degree elevation of periodic rational Bézier curves. We further discuss the editing possibilities given by the trigonometric barycentric form.

Abstract Any point inside a d‐dimensional simplex can be expressed in a unique way as a convex combination of the simplex's vertices, and the coefficients of this combination are called the barycentric coordinates of the point. The idea of barycentric coordinates extends to general polytopes with n vertices, but they are no longer unique if n > d+1. Several constructions of such generalized barycentric coordinates have been proposed, in particular for polygons and polyhedra, but most approaches cannot guarantee the non‐negativity of the coordinates, which is important for applications like image warping and mesh deformation. We present a novel construction of non‐negative and smooth generalized barycentric coordinates for arbitrary simple polygons, which extends to higher dimensions and can include isolated interior points. Our approach is inspired by maximum entropy coordinates, as it also uses a statistical model to define coordinates for convex polygons, but our generalization to non‐convex shapes is different and based instead on the project‐and‐smooth idea of iterative coordinates. We show that our coordinates and their gradients can be evaluated efficiently and provide several examples that illustrate their advantages over previous constructions.

Many popular modern image processing software packages implement a naïve form of histogram equalization. This implementation is known to produce histograms that are not truly uniform. While exact histogram equalization techniques exist, these may produce undesirable artifacts in some scenarios. In this paper we consider the link between the established continuous theory for global histogram equalization and its discrete implementation, and we formulate a novel histogram equalization technique that builds upon and considerably improves the naïve approach. We show that we can linearly interpolate the cumulative distribution of a low-bit image by approximately dequantizing its intensities using a selective box filter. This helps to distribute the intensities more evenly. The proposed algorithm is subsequently evaluated and compared with existing works in the literature. We find that the method is capable of producing an equalized histogram that has a high entropy, while distances between similar intensities are preserved. The described approach has implications on several related image processing problems, e.g., edge detection.

Geodesic distances between pairs of points on a 3D mesh surface are a crucial ingredient of many geometry processing tasks, but are notoriously difficult to compute efficiently on demand. We propose a novel method for the compact storage of geodesic distance information, which enables answering point-to-point geodesic distance queries very efficiently. For a triangle mesh with n vertices, if computing the geodesic distance to all vertices from a single source vertex costs O(f(n)) time, then we generate a database of size O(mnlogn) in O((f(n)+m3n)√n) time in a preprocessing stage, where m is a constant that depends on the geometric complexity of the surface. We achieve this by computing a nested bisection of the mesh surface using separator curves and storing compactly-described functions approximating the distances between each mesh vertex and a small relevant subset of these curves. Using this database, the geodesic distance between two mesh vertices can then be approximated well by solving a small number of simple univariate minimization problems in O(mlogn) worst case time and O(m) average case time. Our method provides an excellent tradeoff between the size of the database, query runtime, and accuracy of the result. It can be used to compress exact or approximate geodesic distances, e.g., those obtained by VTP (exact), fast DGG, fast marching, or the heat method (approximate) and is very efficient if f(n) = n, as for the fast DGG method.

Subdivision schemes are used to generate smooth curves or surfaces by iteratively refining an initial control polygon or mesh. We focus on univariate, linear, binary subdivision schemes, where the vertices of the refined polygon are computed as linear combinations of the current neighbouring vertices. In the classical stationary setting, there are just two such subdivision rules, which are used throughout all subdivision steps to construct the new vertices with even and odd indices, respectively. These schemes are well understood and many tools have been developed for deriving their properties, including the smoothness of the limit curves. For non-stationary schemes, the subdivision rules are not fixed and can be different in each subdivision step. Non-uniform schemes are even more general, as they allow the subdivision rules to be different for every new vertex that is generated by the scheme. The properties of non-stationary and non-uniform schemes are usually derived by relating the scheme to a corresponding stationary scheme and then exploiting the fact that the properties of the stationary scheme carry over under certain proximity conditions. In particular, this approach can be used to show that the limit curves of a non-stationary or non-uniform scheme are as smooth as those of a corresponding stationary scheme. In this paper we show that non-uniform subdivision schemes have the potential to generate limit curves that are smoother than those of stationary schemes with the same support size of the subdivision rule. For that, we derive interpolatory 2-point and 4-point schemes that generate C1 and C2 limit curves, respectively. These values of smoothness exceed the smoothness of classical interpolating schemes with the same support size by one.

Range functions are an important tool for interval computations, and they can be employed for the problem of root isolation. In this paper, we first introduce two new classes of range functions for real functions. They are based on the remainder form by Cornelius and Lohner [7] and provide different improvements for the remainder part of this form. On the one hand, we use centered Taylor expansions to derive a generalization of the classical Taylor form with higher than quadratic convergence. On the other hand, we propose a recursive interpolation procedure, in particular based on quadratic Lagrange interpolation, leading to recursive Lagrange forms with cubic and quartic convergence. We then use these forms for isolating the real roots of square-free polynomials with the algorithm Eval, a relatively recent algorithm that has been shown to be effective and practical. Finally, we compare the performance of our new range functions against the standard Taylor form. Range functions are often compared in isolation; in contrast, our holistic comparison is based on their performance in an application. Specifically, Eval can exploit features of our recursive Lagrange forms which are not found in range functions based on Taylor expansion. Experimentally, this yields at least a twofold speedup in Eval.

Bézier curves are indispensable for geometric modelling and computer graphics. They have numerous favourable properties and provide the user with intuitive tools for editing the shape of a parametric polynomial curve. Even more control and flexibility can be achieved by associating a shape parameter with each control point and considering rational Bézier curves, which comes with the additional advantage of being able to represent all conic sections exactly. In this paper, we explore the editing possibilities that arise from expressing a rational Bézier curve in barycentric form. In particular, we show how to convert back and forth between the Bézier and the barycentric form, we discuss the effects of modifying the constituents (nodes, interpolation points, weights) of the barycentric form, and we study the connection between point insertion in the barycentric form with degree elevation of the Bézier form. Moreover, we analyse the favourable performance of the barycentric form for evaluating the curve.

Abstract We study the landmark distance function between two points in a simply connected planar polygon. We show that if the polygon vertices are used as landmarks, then the resulting landmark distance function to any given point in the polygon has a maximum principle and also does not contain local minima. The latter implies that a path between any two points in the polygon may be generated by steepest descent on this distance without getting “stuck” at a local minimum. Furthermore, if landmarks are increasingly added along polygon edges, the steepest descent path converges to the minimal geodesic path. Therefore, the landmark distance can be used, on the one hand in robotic navigation for routing autonomous agents along close‐to‐shortest paths and on the other for efficiently computing approximate geodesic distances between any two domain points, a property which may be useful in an extension of our work to surfaces in 3D. In the discrete setting, the steepest descent strategy becomes a greedy routing algorithm along the edges of a triangulation of the interior of the polygon, and our experiments indicate that this discrete landmark routing always delivers (i.e., does not get stuck) on “nice” triangulations.

Abstract Path generation is an important problem in many fields, especially robotics. One way to create a path between a source point z and a target point y inside a complex planar domain Ω is to define a non‐negative distance function d(y, z), such that following the negative gradient of d (by z) traces out such a path. This presents two challenges: (1) The mathematical challenge of defining d, such that d(y, z) has a single minimum at z = y for any fixed y, because the gradient‐descent path may otherwise terminate at a local minimum before reaching y; (2) The computational challenge of defining d, such that it can be computed efficiently. Using the concepts of harmonic measure and f‐divergence, we show how to assign a set of reduced coordinates to each point in Ω and to define a family of distance functions based on these coordinates, such that both the mathematical and the computational challenge are met. Since in practice, especially in robotics applications, the path is often restricted to follow the edges of a discrete network defined on a finite set of sites sampled from Ω, any method that works well in the continuous setting must be discretized appropriately to preserve the important properties of the continuous case. We show how to define a network connecting a finite set of sites, such that a greedy routing algorithm, which is the discrete equivalent of continuous gradient descent, based on our reduced coordinates is guaranteed to generate a path in the network between any two sites. In many cases, this network is close to a planar graph, especially if the set of sites is dense. Guaranteeing the existence of a greedy route between any two points in the graph is a significant advantage in practical applications, avoiding the complexity of other path‐planning methods, such as the shortest‐path and A* algorithms. While the paths generated by our algorithm are not the shortest possible, in practice we found that they are close to that.

Barycentric coordinates were introduced by Möbius in 1827 as an alternative to Cartesian coordinates. They describe points relative to the vertices of a simplex and are commonly used to express the linear interpolant of data given at these vertices. Generalized barycentric coordinates and kernels extend this idea from simplices to polyhedra and smooth domains. In this paper, we focus on Wachspress coordinates and Wachspress kernels with respect to strictly convex planar domains. Since Wachspress kernels can be evaluated analytically only in special cases, a common way to approximate them is to discretize the domain by an inscribed polygon and to use Wachspress coordinates, which have a simple closed form. We show that this discretization, which is known to converge quadratically, is safe in the sense that the Wachspress coordinates used in this process are well-defined not only over the inscribed polygon, but over the entire original domain.

Abstract Pseudo‐splines provide a rich family of subdivision schemes with a wide range of choices that meet various demands for balancing the approximation power, the length of the support, and the regularity of the limit functions. Special cases of pseudo‐splines include uniform odd‐degree B‐splines and the interpolatory 2n‐point subdivision schemes, and the other pseudo‐splines fill the gap between these two families. In this paper we show how the refinement step of a pseudo‐spline subdivision scheme can be implemented efficiently using repeated local operations, which require only the data in the direct neighbourhood of each vertex, and how to generalize this concept to quadrilateral meshes with arbitrary topology. The resulting pseudo‐spline surfaces can be arbitrarily smooth in regular mesh regions and C1at extraordinary vertices as our numerical analysis reveals.

Abstract This paper addresses the problem of representing dynamic 3D meshes in a compact way, so that they can be stored and transmitted efficiently. We focus on sequences of triangle meshes with shared connectivity, avoiding the necessity of having a skinning structure. Our method first computes an average mesh of the whole sequence in edge shape space. A discrete geometric Laplacian of this average surface is then used to encode the coefficients that describe the trajectories of the mesh vertices. Optionally, a novel spatio‐temporal predictor may be applied to the trajectories to further improve the compression rate. We demonstrate that our approach outperforms the current state of the art in terms of low data rate at a given perceived distortion, as measured by the STED and KG error metrics.

Barycentric coordinates yield a powerful and yet simple paradigm to interpolate data values on polyhedral domains. They represent interior points of the domain as an affine combination of a set of control points, defining an interpolation scheme for any function defined on a set of control points. Numerous barycentric coordinate schemes have been proposed satisfying a large variety of properties. However, they typically define interpolation as a combination ofallcontrol points. Thus alocalchange in the value at a single control point will create aglobalchange by propagation into the whole domain. In this context, we present a family oflocal barycentric coordinates(LBC), which select for each interior point a small set of control points and satisfy common requirements on barycentric coordinates, such as linearity, non-negativity, and smoothness. LBC are achieved through a convex optimization based on total variation, and provide a compact representation that reduces memory footprint and allows for fast deformations. Our experiments show that LBC provide more local and finer control on shape deformation than previous approaches, and lead to more intuitive deformation results.

Abstract Interpolation between compatible triangle meshes that represent different poses of some object is a fundamental operation in geometry processing. A common approach is to consider the static input shapes as points in a suitable shape space and then use simple linear interpolation in this space to find an interpolated shape. In this paper, we present a new interpolation technique that is particularly tailored for meshes that represent articulated shapes. It is up to an order of magnitude faster than state‐of‐the‐art methods and gives very similar results. To achieve this, our approach introduces a novel shape space that takes advantage of the underlying structure of articulated shapes and distinguishes between rigid parts and non‐rigid joints. This allows us to use fast vertex interpolation on the rigid parts and resort to comparatively slow edge‐based interpolation only for the joints.

Abstract We introduce the novel concept of composite barycentric mappings and give theoretical conditions under which they are guaranteed to be bijective. We then focus on mean value mappings and derive a simple procedure for computing their Jacobians, leading to an efficient GPU‐assisted implementation for interactively designing composite mean value mappings which are bijective up to pixel resolution. We provide a number of examples of 2D image deformation and an example of 3D shape deformation based on a natural extension of the concept to spatial mappings.

Abstract It is increasingly popular to represent non‐rigid motion using a deforming mesh sequence: a discrete sequence of frames, each of which is given as a mesh with a common graph structure. Such sequences have the flexibility to represent a wide range of mesh deformations used in practice, but they are also highly redundant, expensive to store, and difficult to edit in a time‐coherent manner. We address these limitations with a continuous representation that extracts redundancy in three separate phases, leading to separate editable signals in time, pose and shape. The representation can be applied to any deforming mesh sequence, in contrast to previous domain‐specific approaches. By modifying the three signal components, we demonstrate time‐coherent editing operations such as local repetition of part of a sequence, frame rate conversion and deformation transfer. We also show that our representation makes it possible to design new deforming sequences simply by sketching a curve in a 2D pose space.

Abstract Barycentric coordinates are very popular for interpolating data values on polyhedral domains. It has been recently shown that expressing them as complex functions has various advantages when interpolating two‐dimensional data in the plane, and in particular for holomorphic maps. We extend and generalize these results by investigating the complex representation of real‐valued barycentric coordinates, when applied to planar domains. We show how the construction for generating real‐valued barycentric coordinates from a given weight function can be applied to generating complex‐valued coordinates, thus deriving complex expressions for the classical barycentric coordinates: Wachspress, mean value, and discrete harmonic. Furthermore, we show that a complex barycentric map admits the intuitive interpretation as a complex‐weighted combination of edge‐to‐edge similarity transformations, allowing the design of “home‐made” barycentric maps with desirable properties. Thus, using the tools of complex analysis, we provide a methodology for analyzing existing barycentric mappings, as well as designing new ones.

Abstract Interpolating vertex positions among triangle meshes with identical vertex‐edge graphs is a fundamental part of many geometric modelling systems. Linear vertex interpolation is robust but fails to preserve local shape. Most recent approaches identify local affine transformations for parts of the mesh, model desired interpolations of the affine transformations, and then optimize vertex positions to conform with the desired transformations. However, the local interpolation of the rotational part is non‐trivial for more than two input configurations and ambiguous if the meshes are deformed significantly. We propose a solution to the vertex interpolation problem that starts from interpolating the local metric (edge lengths) and mean curvature (dihedral angles) and makes consistent choices of local affine transformations using shape matching applied to successively larger parts of the mesh. The local interpolation can be applied to any number of input vertex configurations and due to the hierarchical scheme for generating consolidated vertex positions, the approach is fast and can be applied to very large meshes.

We present a method for parameterizing subdivision surfaces in an as-rigid-as-possible fashion. While much work has concentrated on parameterizing polygon meshes, little if any work has focused on subdivision surfaces despite their popularity. We show that polygon parameterization methods produce suboptimal results when applied to subdivision surfaces and describe how these methods may be modified to operate on subdivision surfaces. We also describe a method for creating extended charts to further reduce the distortion of the parameterization. Finally we demonstrate how to take advantage of the multi-resolution structure of subdivision surfaces to accelerate convergence of our optimization.

Mesh parameterization is a powerful geometry processing tool with numerous computer graphics applications, from texture mapping to animation transfer. This course outlines its mathematical foundations, describes recent methods for parameterizing meshes over various domains, discusses emerging tools like global parameterization and inter-surface mapping, and demonstrates a variety of parameterization applications.

Abstract Barycentric coordinates can be used to express any point inside a triangle as a unique convex combination of the triangle's vertices, and they provide a convenient way to linearly interpolate data that is given at the vertices of a triangle. In recent years, the ideas of barycentric coordinates and barycentric interpolation have been extended to arbitrary polygons in the plane and general polytopes in higher dimensions, which in turn has led to novel solutions in applications like mesh parameterization, image warping, and mesh deformation. In this paper we introduce a new generalization of barycentric coordinates that stems from the maximum entropy principle. The coordinates are guaranteed to be positive inside any planar polygon, can be evaluated efficiently by solving a convex optimization problem with Newton's method, and experimental evidence indicates that they are smooth inside the domain. Moreover, the construction of these coordinates can be extended to arbitrary polyhedra and higher‐dimensional polytopes.

Fluid simulations typically produce complex three-dimensional (3D) isosurfaces whose geometry and topology change over time. The standard way of representing such "dynamic geometry" is by a set of isosurfaces that are extracted individually at certain time steps. An alternative strategy is to represent the whole sequence as a four-dimensional (4D) tetrahedral mesh. The iso-surface at a specific time step can then be computed by intersecting the tetrahedral mesh with a 3D hyperplane. This not only allows the animation of the surface continuously over time without having to worry about the topological changes, but also enables simplification algorithms to exploit temporal coherence. We show how to interactively render such 4D tetrahedral meshes by improving previous GPU-accelerated techniques and building an out-of-core multi-resolution structure based on quadric error simplification. As a second application, we apply our framework to time-varying surfaces that result from morphing one triangle mesh into another.

Barycentric coordinates for triangles are commonly used in computer graphics, geometric modeling, and other computational sciences because they provide a convenient way to linearly interpolate the data that is given at the corners of a triangle. The concept of barycentric coordinates can also be extended in several ways to convex polygons with more than three vertices, but most of these constructions break down when used in the nonconvex setting.Mean value coordinatesoffer a choice that is not limited to convex configurations, and we show that they are in fact well-defined for arbitrary planar polygons without self-intersections. Besides their many other important properties, these coordinate functions are smooth and allow an efficient and robust implementation. They are particularly useful for interpolating data that is given at the vertices of the polygons and we present several examples of their application to common problems in computer graphics and geometric modeling.

Standard texture mapping of real-world meshes suffers from the presence of seams that need to be introduced in order to avoid excessive distortions and to make the topology of the mesh compatible to the one of the texture domain. In contrast, cube maps provide a mechanism that could be used for seamless texture mapping with low distortion, but only if the object roughly resembles a cube. We extend this concept to arbitrary meshes by using as texture domain the surface of a polycube whose shape is similar to that of the given mesh. Our approach leads to a seamless texture mapping method that is simple enough to be implemented in currently available graphics hardware.

The importance of triangle meshes with a special kind of connectivity, the so-called subdivision connectivity is still growing. Therefore it is important to develop efficient algorithms for converting a given mesh with arbitrary connectivity into one with subdivision connectivity. We focus on 2-manifold triangle meshes with a boundary and no holes. We discuss the importance of a parametrization with minimal distortion for the process of remeshing. Based on the concept of most isometric parameterizations we have developed a remeshing algorithm for the given class of triangle meshes. A series of examples shows the advantages of our approach.

Clipping 2D polygons is one of the basic routines in computer graphics. In rendering complex 3D images it has to be done several thousand times. Efficient algorithms are therefore very important. We present such an efficient algorithm for clipping arbitrary 2D-polygons. The algorithm can handle arbitrary closed polygons, specifically where the clip and subject polygons may self-intersect. The algoirthm is simple and faster that Vatti's (1992) algorithm, which was designed for the general case as well. Simple modifications allow determination of union and set-theoretic differences of two arbitrary polygons.