IEEE VIS Publication Dataset

This paper presents efficient image-based rendering techniques used in the context of an architectural walkthrough system. Portals (doors and windows) are rendered by warping layered depth images (LDIs). In a preprocessing phase, for every portal, a number of pre-rendered images are combined into an LDI. The resulting LDI stores, exactly once, all surfaces visible in at least one of the images used in the construction, so most of the exposure errors are efficiently eliminated. The LDI can be warped in the McMillan occlusion compatible ordering. A substantial increase in performance is obtained by warping in parallel. Our parallelization scheme achieves good load balancing, scales with the number of processors, and preserves the occlusion compatible ordering. A fast, conservative reference-image-space clipping algorithm also reduces the warping effort.

Splatting is a fast volume rendering algorithm which achieves its speed by projecting voxels in the form of pre-integrated interpolation kernels, or splats. Presently, two main variants of the splatting algorithm exist: (i) the original method, in which all splats are composited back-to-front, and (ii) the sheet-buffer method, in which the splats are added in cache-sheets, aligned with the volume face most parallel to the image plane, which are subsequently composited back-to-front. The former method is prone to cause bleeding artifacts from hidden objects, while the latter method reduces bleeding, but causes very visible color popping artifacts when the orientation of the compositing sheets changes suddenly as the image screen becomes more parallel to another volume face. We present a new variant of the splatting algorithm in which the compositing sheets are always parallel to the image plane, eliminating the condition for popping, while maintaining the insensitivity to color bleeding. This enables pleasing animated viewing of volumetric objects without temporal color and lighting discontinuities. The method uses a hierarchy of partial splats and employs an efficient list-based volume traversal scheme for fast splat access. It also offers more accuracy for perspective splatting as the decomposition of the individual splats facilitates a better approximation to the diverging nature of the rays that traverse the splatting kernels.

We are interested in feature extraction from volume data in terms of coherent surfaces and 3D space curves. The input can be an inaccurate scalar or vector field, sampled densely or sparsely on a regular 3D grid, in which poor resolution and the presence of spurious noisy samples make traditional iso-surface techniques inappropriate. In this paper, we present a general-purpose methodology to extract surfaces or curves from a digital 3D potential vector field {(s,v~)}, in which each voxel holds a scalar s designating the strength and a vector v~ indicating the direction. For scalar, sparse or low-resolution data, we "vectorize" and "densify" the volume by tensor voting to produce dense vector fields that are suitable as input to our algorithms, the extremal surface and curve algorithms. Both algorithms extract, with sub-voxel precision, coherent features representing local extrema in the given vector field. These coherent features are a hole-free triangulation mesh (in the surface case), and a set of connected, oriented and non-intersecting polyline segments (in the curve case). We demonstrate the general usefulness of both extremal algorithms on a variety of real data by properly extracting their inherent extremal properties, such as (a) shock waves induced by abrupt velocity or direction changes in a flow field, (b) interacting vortex cores and vorticity lines in a velocity field, (c) crest-lines and ridges implicit in a digital terrain map, and (d) grooves, anatomical lines and complex surfaces from noisy dental data.

Conventional wisdom says that in order to produce high-quality simplified polygonal models, one must retain and use information about the original model during the simplification process. We demonstrate that excellent simplified models can be produced without the need to compare against information from the original geometry while performing local changes to the model. We use edge collapses to perform simplification, as do a number of other methods. We select the position of the new vertex so that the original volume of the model is maintained and we minimize the per-triangle change in volume of the tetrahedra swept out by those triangles that are moved. We also maintain surface area near boundaries and minimize the per-triangle area changes. Calculating the edge collapse priorities and the positions of the new vertices requires only the face connectivity and the the vertex locations in the intermediate model. This approach is memory efficient, allowing the simplification of very large polygonal models, and it is also fast. Moreover, simplified models created using this technique compare favorably to a number of other published simplification methods in terms of mean geometric error.

A novel approach is introduced to define a quantitative measure of closeness between vector fields. The usefulness of this measurement can be seen when comparing computational and experimental flow fields under the same conditions. Furthermore, its applicability can be extended to more cumbersome tasks, such as navigating through a large database, searching for similar topologies. This new measure relies on the use of critical points, which are a key feature in vector field topology. In order to characterize critical points, α and β parameters are introduced. They are used to form a closed set of eight unique patterns for simple critical points. These patterns are also basic building blocks for higher-order nonlinear vector fields. In order to study and compare a given set of vector fields, a measure of distance between different patterns of critical points is introduced. The basic patterns of critical points are mapped onto a unit circle in α-β space. The concept of the "Earth mover's distance" is used to compute the closeness between various pairs of vector fields, and a nearest-neighbor query is thus produced to illustrate the relationship between the given set of vector fields. This approach quantitatively measures the similarity and dissimilarity between vector fields. It is ideal for data compression of a large flow field, since only the number and types of critical points along with their corresponding α and β parameters are necessary to reconstruct the whole field. It can also be used to better quantify the changes in time-varying data sets.

This paper describes by example a strategy for plotting and interacting with data in multiple metric spaces. The example system was designed for use with time-varying computational fluid dynamics (CFD) data sets, but the methodology is directly applicable to other types of field data. The central objects embodied by the tool are portraits, which show the data in various coordinate systems, while preserving their spatial connectivity and temporal variability. The coordinates are derived in various ways from the field data, and an important feature is that new and derived portraits can be created interactively. The primary operations supported by the tool are brushing and linking: the user can select a subset of a given portrait, and this subset is highlighted in all portraits. The user can combine highlighted subsets from an arbitrary number of portraits with the usual logical operators, thereby indicating where an arbitrarily complex set of conditions holds. The system is useful for exploratory visualization and feature detection in multivariate data.

One common problem in the practical application of volume visualization is the proper choice of transfer functions in order to color different parts of the volume meaningfully. This interactive process can be very complicated and time consuming. An alternative to the adjustment of transfer functions is the application of segmentation algorithms. These algorithms are often dedicated to a limited range of data sets and tend to be very compute intensive. We propose a morphology based hierarchical analysis to estimate the optical properties of the volume to be rendered. This approach requires fewer parameters and incorporates also spatial information, but it is far less compute intensive than most of the segmentation methods. The hierarchical analysis is constructed in analogy to the wavelet analysis, except for the fact, that nonlinear filters are used in our case. These morphological operators have a lower distortional influence on the analyzed structures than the usual linear filters. A special decomposition of the morphological operators is discussed, which leads to an efficient implementation of this approach. This technique reduces the three dimensional analysis to a one dimensional computation, as it is done in tensor product based linear filters. The resulting decomposition may also be parallelized easily. We demonstrate the usefulness of the proposed technique by applying it to medical and technical data sets.

For high quality rendering of objects segmented from tomographic volume data the precise location of the boundaries of adjacent objects in subvoxel resolution is required. We describe a new method that determines the membership of a given sample point to an object by reclassifying the sample point using interpolation of the original intensity values and searching for the best fitting object in the neighbourhood. Using a ray-casting approach we then compute the surface location between successive sample points along the viewing-ray by interpolation or bisection. The accurate calculation of the object boundary enables a much more precise computation of the gray-level-gradient yielding the surface normal. Our new approach significantly improves the quality of reconstructed and shaded surfaces and reduces aliasing artifacts for animations and magnified views. We illustrate the results on different cases including the Visible-Human-Data, where we achieve nearly photo-realistic images.

We attack the problem of image based rendering with occlusions and general camera motions by using distorted multiperspective images; such images provide multiple viewpoint photometry similar to the paintings of cubist artists. We take scene geometry, in contrast, to be embodied in mappings of viewing rays from their original 3D intercepts into the warped multiperspective image space. This approach allows us to render approximations of scenes with occlusions using time dense and spatially sparse sequences of camera rays, which is a significant improvement over the storage requirements of an equivalent animation sequence. Additional data compression can be achieved using sparse time keyframes as well. Interpolating the paths of sparse time key rays correctly in image space requires singular interpolation functions with spatial discontinuities. While there are many technical questions yet to be resolved, the employment of these singular interpolation functions in the multiperspective image space appears to be of potential interest for generating general viewpoint scene renderings with minimal data storage.

Transfer function design is an integrated component in volume visualization and data exploration. The common trial-and-error approach for transfer function searching is a very difficult and time consuming process. A goal oriented and parameterized transfer function model is therefore crucial in guiding the transfer function searching process for better and more meaningful visualization results. The paper presents an image based transfer function model that integrates 3D image processing tools into the volume visualization pipeline to facilitate the search for an image based transfer function in volume data visualization and exploration. The model defines a transfer function as a sequence of 3D image processing procedures, and allows the users to adjust a set of qualitative and descriptive parameters to achieve their subjective visualization goals. 3D image enhancement and boundary detection tools, and their integration methods with volume visualization algorithms are described. The application of this approach for 3D microscopy data exploration and analysis is also discussed.

The success of using a streamline technique for visualizing a vector field usually depends largely on the choice of adequate seed points. G. Turk and D. Banks (1996) developed an elegant technique for automatically placing seed points to achieve a uniform distribution of streamlines on a 2D vector field. Their method uses an energy function calculated from the low-pass filtered streamline image to guide the optimization process of the streamline distribution. This paper proposes a new technique for creating evenly distributed streamlines on 3D parametric surfaces found in curvilinear grids. We make use of Turk and Banks's 2D algorithm by first mapping the vectors on a 3D surface into the computational space of the curvilinear grid. To take into the consideration the mapping distortion caused by the uneven grid density in a curvilinear grid, a new energy function is designed and used for guiding the placement of streamlines in the computational space with desired local densities.

This paper considers how out-of-core visualization applies to terrain datasets, which are among the largest now presented for interactive visualization and can range to sizes of 20 GB and more. It is found that a combination of out-of-core visualization, which tends to focus on 3D data, and visual simulation, which places an emphasis on visual perception and real-time display of multiresolution data, results in interactive terrain visualization with significantly improved data access and quality of presentation. Further, the visual simulation approach provides qualities that are useful for general data, not just terrain.

This paper presents techniques for interactively visualizing tensor fields using deformations. The conceptual idea behind this approach is to allow the tensor field to manifest its influence on idealized objects placed within the tensor field. This is similar, though not exactly the same, to surfaces deforming under load in order to relieve built up stress and strain. We illustrate the effectiveness of the Deviator-Isotropic tensor decomposition in deformation visualizations of CFD strain rate. We also investigate how directional flow techniques can be extended to distinguish between regions of tensile versus compressive forces.

Large textures cause bottlenecks in real time applications that often lead to a loss of interactivity. These performance bottlenecks occur because of disk and network transfer, texture translation, and memory swapping. We present a software solution that alleviates the problems associated with large textures by treating texture as a bandwidth limited resource rather than a finite resource. As a result the display of large textures is reduced to a caching problem in which texture memory serves as the primary cache for texture data, main memory the secondary cache, and local disk the tertiary cache. By using this cache hierarchy, applications are able to maintain real time performance while displaying textures hundreds of times larger than can fit into texture memory.

We present a novel out-of-core technique for the interactive computation of isosurfaces from volume data. Our algorithm minimizes the main memory and disk space requirements on the visualization workstation, while speeding up isosurface extraction queries. Our overall approach is a two-level indexing scheme. First, by our meta-cell technique, we partition the original dataset into clusters of cells, called meta-cells. Secondly, we produce meta-intervals associated with the meta-cells, and build an indexing data structure on the meta-intervals. We separate the cell information, kept only in meta-cells on disk, from the indexing structure, which is also on disk and only contains pointers to meta-cells. Our meta-cell technique is an I/O-efficient approach for computing a k-d-tree-like partition of the dataset. Our indexing data structure, the binary blocked I/O interval tree, is a new I/O-optimal data structure to perform stabbing queries that report from a set of meta-intervals (or intervals) those containing a query value q. Our tree is simpler to implement, and is also more space-efficient in practice than existing structures. To perform an isosurface query, we first query the indexing structure, and then use the reported meta-cell pointers to read from disk the active meta-cells intersected by the isosurface. The isosurface itself can then be generated from active meta-cells. Rather than being a single cost indexing approach, our technique exhibits a smooth trade-off between query time and disk space.

We show that it is feasible to perform interactive isosurfacing of very large rectilinear datasets with brute-force ray tracing on a conventional (distributed) shared-memory multiprocessor machine. Rather than generate geometry representing the isosurface and render with a z-buffer, for each pixel we trace a ray through a volume and do an analytic isosurface intersection computation. Although this method has a high intrinsic computational cost, its simplicity and scalability make it ideal for large datasets on current high-end systems. Incorporating simple optimizations, such as volume bricking and a shallow hierarchy, enables interactive rendering (i.e. 10 frames per second) of the 1 GByte full resolution Visible Woman dataset on an SGI Reality Monster. The graphics capabilities of the Reality Monster are used only for display of the final color image.

Virtual angioscopy is a non invasive medical procedure for exploring parts of the human vascular system. We have developed an interactive tool that takes as input, data acquired with standard medical imaging modalities and regards it as a virtual environment to be interactively inspected. The system supports real time navigation with stereoscopic direct volume rendering and dynamic endoscopic camera control, interactive tissue classification, and interactive point picking for morphological feature measurement. We provide an overview of the system, discuss the techniques used in our prototype, and present experimental results on human data sets.

We consider interpolation between keyframe hierarchies. We impose a set of weak constraints that allows smooth interpolation between two keyframe hierarchies in an animation or, more generally, allows the interpolation in an n-parameter family of hierarchies. We use hierarchical triangulations obtained by the Rivara element bisection algorithm (M. Rivara, 1984) and impose a weak compatibility constraint on the set of root elements of all keyframe hierarchies. We show that the introduced constraints are rather weak. The strength of our approach is that the interpolation works in the class of conforming triangulations and simplifies the task of finding the intermediate hierarchy, which is the union of the two (or more) keyframe hierarchies involved in the interpolation process. This allows for an efficient generation of the intermediate connectivity and additionally ensures that the intermediate hierarchy is again a conforming hierarchy satisfying the same constraints.

Many high-performance isosurface extraction algorithms have been proposed in the past several years as a result of intensive research efforts. When applying these algorithms to large-scale time-varying fields, the storage overhead incurred from storing the search index often becomes overwhelming. This paper proposes an algorithm for locating isosurface cells in time-varying fields. We devise a new data structure, called the temporal hierarchical index tree, which utilizes the temporal coherence that exists in a time-varying field and adaptively coalesces the cells' extreme values over time; the resulting extreme values are then used to create the isosurface cell search index. For a typical time-varying scalar data set, not only does this temporal hierarchical index tree require much less storage space, but also the amount of I/O required to access the indices from the disk at different time steps is substantially reduced. We illustrate the utility and speed of our algorithm with data from several large-scale time-varying CFD simulations. Our algorithm can achieve more than 80% of disk-space savings when compared with the existing techniques, while the isosurface extraction time is nearly optimal.