Volume rendering is a technique for visualizing 3D arrays of sampled data. It has applications in areas such as medical imaging and scientific visualization, but its use has been limited by its high computational expense. Early implementations of volume rendering used brute-force techniques that require on the order of 100 seconds to render typical data sets on a workstation. Algorithms with optimizations that exploit coherence in the data have reduced rendering times to the range of ten seconds but are still not fast enough for interactive visualization applications. In this thesis we present a family of volume rendering algorithms that reduces rendering times to one second. First we present a scanline-order volume rendering algorithm that exploits coherence in both the volume data and the image. We show that scanline-order algorithms are fundamentally more efficient than commonly-used ray casting algorithms because the latter must perform analytic geometry calculations (e.g. intersecting rays with axis-aligned boxes). The new scanline-order algorithm simply streams through the volume and the image in storage order. We describe variants of the algorithm for both parallel and perspective projections and

Traditionally, shape transformation using implicit functions is performed in two distinct steps: 1) creating two implicit functions, and 2) interpolating between these two functions. We present a new shape transformation method that combines these two tasks into a single step. We create a transformation between two N- dimensional objects by casting this as a scattered data interpolation problem in N + 1 dimensions. For the case of 2D shapes, we place all of our data constraints within two planes, one for each shape. These planes are placed parallel to one another in 3D. Zero-valued constraints specify the locations of shape boundaries and positivevalued constraints are placed along the normal direction in towards the center of the shape. We then invoke a variational interpolation technique (the 3D generalization of thin-plate interpolation), and this yields a single implicit function in 3D. Intermediate shapes are simply the zero-valued contours of 2D slices through this 3D function. Shape transformation between 3D shapes can be performed similarly by solving a 4D interpolation problem. To our knowledge, ours is the first shape transformation method to unify the tasks of implicit function creation and interpolation. The transformations produced by this method appear smooth and natural, even between objects of differing topologies. If desired, one or more additional shapes may be introduced that influence the intermediate shapes in a sequence. Our method can also reconstruct surfaces from multiple slices that are not restricted to being parallel to one another.

Abstract not found

We present a new method for user controlled morphing of two homeomorphic triangle meshes of arbitrary topology. In particular we focus on the problem of establishing a correspondence map between source and target meshes. Our method employs the MAPS algorithm to parameterize both meshes over simple base domains and an additional harmonic map bringing the latter into correspondence. To control the mapping the user specifies any number of feature pairs, which control the parameterizations produced by the MAPS algorithm. Additional controls are provided through a direct manipulation interface allowing the user to tune the mapping between the base domains. We give several examples of sthetically pleasing morphs which can be created in this manner with little user input. Additionally we demonstrate examples of temporal and spatial control over the morph.

We present a method for applying complex textures to hand-drawn characters in cel animation. The method correlates features in a simple, textured, 3-D model with features on a hand-drawn figure, and then distorts the model to conform to the hand-drawn artwork. The process uses two new algorithms: a silhouette detection scheme and a depth-preserving warp. The silhouette detection algorithm is simple and efficient, and it produces continuous, smooth, visible contours on a 3-D model. The warp distorts the model in only two dimensions to match the artwork from a given camera perspective, yet preserves 3-D effects such as self-occlusion and foreshortening. The entire process allows animators to combine complex textures with hand-drawn artwork, leveraging the strengths of 3-D computer graphics while retaining the expressiveness of traditional handdrawn cel animation.

We present a new approach for establishing correspondence between two homeomorphic 3D polyhedral models. The user can specify corresponding feature pairs on the polyhedra with a simple and intuitive interface. Based on these features, our algorithm decomposes the boundary of each polyhedron into the same number of morphing patches. A 2D mapping for each morphing patch is computed in order to merge the topologies of the polyhedra one patch at a time. We create a morph by defining morphing trajectories between the feature pairs and by interpolating them across the merged polyhedron. The user interface provides high-level control as well as local refinement to improve the morph. The implementation has been applied to several complex polyhedra composed of thousands of polygons. The system can also handle non-simple polyhedra that have holes.

This paper presents a framework for generating smooth-looking transformations between pairs of surfaces that may differ in topology. The user controls the transformation by specifying a sparse control mesh on each surface and by associating each face in one control mesh with a corresponding face in the other. The algorithm builds a transformation from this information in two steps. The first step constructs a series of shapes and meshes (according the theory of topological surgery) that describes how topological changes should occur at critical points during the transformation. This makes possible the second step, which establishes smooth transformations by combining intermediate shapes in this series. Control meshes allow the user precise but intuitive control of the morph, while the 3D surfaces that result can be used for rendering or keyframing.

Abstract not found

This article addresses the problem of controlling the density and dynamics of smoke (a gas phenomenon) so that the synthetic appearance of the smoke (gas) resembles a still or moving object. Both the smoke region and the target object are represented as implicit functions. As a part of the target implicit function, a shape transformation is generated between an initial smoke region and the target object. In order to match the smoke surface with the target surface, we impose carefully designed velocity constraints on the smoke boundary during a dynamic fluid simulation. The velocity constraints are derived from an iterative functional minimization procedure for shape matching. The dynamics of the smoke is formulated using a novel compressible fluid model which can effectively absorb the discontinuities in the velocity field caused by imposed velocity constraints while reproducing realistic smoke appearances. As a result, a smoke region can evolve into a regular object and follow the motion of the object, while maintaining its smoke appearance.

In this paper, we introduce the concept of spatial transfer functions as a unified approach to volume modeling and animation. A spatial transfer function is a function that defines the geometrical transformation of a scalar field in space, and is a generalization and abstraction of a variety of deformation methods. It facilitates a field-based representation, and can thus be embedded into a volumetric scene graph under the algebraic framework of constructive volume geometry. We show that when spatial transfer functions are treated as spatial objects, constructive operations and conventional transfer functions can be applied to such spatial objects. We demonstrate spatial transfer functions in action with the aid of a collection of examples in volume visualization, sweeping, deformation and animation. In association with these example, we describe methods for modeling and realizing spatial transfer functions, including simple procedural functions, operational decomposition of complex functions, large scale domain decomposition and temporal spatial transfer functions. We also discuss the implementation of spatial transfer functions in the vlib API and our efforts in deploying the technique in volume animation.