Skilled artists, using traditional media or modern computer painting tools, can create a variety of expressive styles that are very appealing in still images, but have been unsuitable for animation. The key difficulty is that existing techniques lack adequate temporal coherence to animate these styles effectively. Here we augment the range of practical animation styles by extending the guided texture synthesis method of Image Analogies [Hertzmann et al. 2001] to create temporally coherent animation sequences. To make the method art directable, we allow artists to paint portions of keyframes that are used as constraints. The in-betweens calculated by our method maintain stylistic continuity and yet change no more than necessary over time.

We present a new algorithm for identifying the distribution of different material types in volumetric datasets such as those produced with magnetic resonance imaging (MRI) or computed tomography (CT). Because we allow for mixtures of materials and treat voxels as regions, our technique reduces errors that other classification techniques can create along boundaries between materials and is particularly useful for creating accurate geometric models and renderings from volume data. It also has the potential to make volume measurements more accurately and classifies noisy, low-resolution data well. There are two unusual aspects to our approach. First, we assume that, due to partial-volume effects, or blurring, voxels can contain more than one material, e.g., both muscle and fat; we compute the relative proportion of each material in the voxels. Second, we incorporate information from neighboring voxels into the classification process by reconstructing a continuous function, rho(x), from the samples and then looking at the distribution of values that rho(x) takes on within the region of a voxel. This distribution of values is represented by a histogram taken over the region of the voxel; the mixture of materials that those values measure is identified within the voxel using a probabilistic Bayesian approach that matches the histogram by finding the mixture of materials within each voxel most likely to have created the histogram. The size of regions that we classify is chosen to match the spacing of the samples because the spacing is intrinsically related to the minimum feature size that the reconstructed continuous function can represent.

This paper describes the various artistic effects of watercolor and shows how they can be simulated automatically.Our watercolor model is based on an ordered set of translucent glazes, which are created independently using a shallow-water fluid simulation.We use a Kubelka-Munk compositing model for simulating the optical effect of the superimposed glazes.We demonstrate how computergenerated watercolor can be used in three different applications: as part of an interactive watercolor paint system, as a method for automatic image "watercolorization," and as a mechanism for nonphotorealistic rendering of three-dimensional scenes.

We proposean approach for modeling surface details such as scales, feathers, or thorns. These types of cellular textures require a representation with more detail than texture-mapping but are inconvenient to model with hand-crafted geometry. We generate patterns of geometric elements using a biologically -motivated cellular development simulation together with a constraint to keep the cells on a surface. The surface may be defined by an implicit function, a volume dataset, or a polygonal mesh. Our simulation combines and extends previous work in developmental models and constrained particle systems. Key Words: particle systems, developmental models, data amplification, constraints, texture mapping, bump mapping, displacement mapping 1 Introduction For several years computer graphics researchers and practitioners have been grappling with the problem of creating and displaying surfaces having an organic appearance. Texture maps, bump maps, and related methods often attain the appearanc...

Here, the authors combine a pure phase-encoded magnetic resonance imaging (MRI) method with a new tissue-classification technique to make geometric models of a human tooth. They demonstrate the feasibility of three-dimensional imaging of solids using a conventional 11.7-T NMR spectrometer. In solid-state imaging, confounding line-broadening effects are typically eliminated using coherent averaging methods. Instead, the authors circumvent them by detecting the proton signal at a fixed phase-encode time following the radio-frequency excitation. By a judicious choice of the phase-encode time in the MRI protocol, the authors differentiate enamel and dentine sufficiently to successfully apply a new classification algorithm. This tissue-classification algorithm identifies the distribution of different material types, such as enamel and dentine, in volumetric data. In this algorithm, the authors treat a voxel as a volume, not as a single point, and assume that each voxel may contain more than one material. They use the distribution of MR image intensities within each voxel-sized volume to estimate the relative proportion of each material using a probabilistic approach. This combined approach, involving MRI and data classification, is directly applicable to bone imaging and hard-tissue contrast-based modeling of biological solids.

We present an efficient and robust algorithm for finding points of collision between time-dependent parametric and implicit surfaces. The algorithm detects simultaneous collisions at multiple points of contact. When the regions of contact form curves or surfaces, it returns a finite set of points uniformly distributed over each contact region. Collisions can be computed for a very general class of surfaces: those for which inclusion functions can be constructed. Included in this set are the familiar kinds of surfaces and time behaviors encountered in computer graphics. We use a new interval approach for constrained minimization to detect collisions, and a tangency condition to reduce the dimensionality of the search space. These approaches make interval methods practical for multi-point collisions between complex surfaces. An interval Newton method based on the solution of the interval linear equation is used to speed convergence to the collision time and location. This method is mor...

Abstract We develop physically‐based graphics models of non‐rigid objects capable of heat conduction, thermoelasticity, melting and fluid‐like behaviour in the molten state. These deformable models feature non‐rigid dynamics governed by Lagrangian equations of motion and conductive heat transfer governed by the heat equation for non‐homogeneous, non‐isotropic media. In its solid state, the discretized model is an assembly of hexahedral finite elements in which thermoelastic units interconnect particles situated in a lattice. The stiffness of a thermoelastic unit decreases as its temperature increases, and the unit fuses when its temperature exceeds the melting point. The molten state of the model involves a molecular dynamics simulation in which ‘fluid’ particles that have broken free from the lattice interact through long‐range attraction forces and short‐range repulsion forces. We present a physically‐based animation of a thermoelastic model in a simulated physical world populated by hot constraint surfaces.

We continue our development of physically-based models for animating nonrigid objects in simulated physical environments. Our prior work treats the special case of objects that undergo perfectly elastic deformations. Real materials, however, exhibit a rich variety of inelastic phenomena. For instance, objects may restore themselves to their natural shapes slowly, or perhaps only partially upon removal of forces that cause deformation. Moreover, the deformation may depend on the history of applied forces. The present paper proposes inelastically deformable models for use in computer graphics animation. These dynamic models tractably simulate three canonical inelastic behaviors---viscoelasticity, plasticity, and fracture. Viscous and plastic processes within the models evolve a reference component, which describes the natural shape, according to yield and creep relationships that depend on applied force and/or instantaneous deformation. Simple fracture mechanics result from internal processes that introduce local discontinuities as a function of the instantaneous deformations measured through the model. We apply our inelastically deformable models to achieve novel computer graphics effects.

The theory of elasticity describes deformable materials such as rubber, cloth, paper, and flexible metals. We employ elasticity theory to construct differential equations that model the behavior of non-rigid curves, surfaces, and solids as a function of time. Elastically deformable models are active: they respond in a natural way to applied forces, constraints, ambient media, and impenetrable obstacles. The models are fundamentally dynamic and realistic animation is created by numerically solving their underlying differential equations. Thus, the description of shape and the description of motion are unified.

A simple but general approach to imposing and solving geometric constraints on parameterized models is introduced, applicable to animation as well as model construction. Constraints are expressed as energy functions, and the energy gradient followed through the model's parameter space. Intuitively, energy constraints behave like forces that pull and parametrically deform the parts of the model into place. A wide variety of geometric constraints are amenable to this formulation, and may be used to influence arbitrary model parameters. A catalogue of basic constraints is presented, and results are shown. Keywords --- Constraints, Modeling, Animation 1 Introduction A widely-used approach to modeling is to combine geometric primitives---such as cylinders, blocks, and bicubic patches---with a variety of operators---such as translations, rotations, booleans, and deformations--- to form a model hierarchy. The task of constructing a model within this framework has two parts: building the hie...