IEEE VIS Publication Dataset

This paper presents a novel use of visualization applied to debugging the Cplant TM cluster hardware at Sandia National Laboratories. As commodity cluster systems grow in popularity and grow in size, tracking component failures within the hardware will become more and more difficult. We have developed a tool that facilitates visual debugging of errors within the switches and cables connecting the processors. Combining an abstract system model with color-coding for both error and job information enables failing components to be identified.

The Relativistic Heavy Ion Collider (RHIC) experiment at the Brookhaven National Lab is designed to study how the universe came into being. It is believed that after the Big Bang, the universe expanded and cooled, consisting of a soup of quarks, gluons, electrons and neutrinos. As the temperature lowered, electrons combined with protons and formed neutral atoms. Later, clouds of atoms contracted into stars. In this paper, we describe how techniques of volume rendering and information visualization are used to visualize the large particle track data set generated from this high energy physics experiment. The system, called TrackVis, is based on our earlier work of VolVis - Volume Visualization software. Example images of real particle collision data are shown, which are helpful to physicists in investigating the behavior of strongly interacting matter at high energy density.

We present the first algorithm that employs hardware-accelerated cell-projection for direct volume rendering of cyclic meshes, i.e., meshes with visibility cycles. The visibility sorting of a cyclic mesh is performed by an extended topological sorting, which computes and isolates visibility cycles. Measured sorting times are comparable to previously published algorithms, which are, however, restricted to acyclic meshes. In practice, our algorithm is also useful for acyclic meshes as numerical instabilities can lead to false visibility cycles. Our method includes a simple, hardware-assisted algorithm based on image compositing that renders visibility cycles correctly. For tetrahedral meshes this algorithm allows us to render each tetrahedral cell (whether it is part of a cycle or not) by hardware-accelerated cell-projection. In its basic form our method applies only to convex cyclic meshes; however, we present an exact and a simpler but inexact extension of our method for nonconvex meshes.

In this case study we discuss an interactive feature tracking system and its use for the analysis of chromatin decondensation. Features are described as points in a multidimensional attribute space. Distances between points are used as a measure for feature correspondence. Users can interactively experiment with the correspondence measure in order to gain insight in chromatin movement. In addition, by defining time as an attribute, tracking problems related to noisy confocal data can be circumvented.

We present the circular incident edge lists (CIEL), a new data structure and a high-performance algorithm for generating a series of iso-surfaces in a highly unstructured grid. Slicing-based volume rendering is also considered. The CIEL data structure represents all the combinatorial information of the grid, making it possible to optimize the classical propagation from local minima paradigm. The usual geometric structures are replaced by a more efficient combinatorial structure. An active edges list is maintained, and iteratively propagated from an iso-surface to the next one in a very efficient way. The intersected cells incident to each active edge are retrieved, and the intersection polygons are generated by circulating around their facets. This latter feature enables arbitrary irregular cells to be treated, such as those encountered in certain computational fluid dynamics (CFD) simulations. Since the CIEL data structure solely depends on the connections between the cells, it is possible to take into account dynamic changes in the geometry of the mesh and in property values, which only requires the sorted extrema list to be updated. Experiments have shown that our approach is significantly faster than classical methods. The major drawback of our method is its memory consumption, higher than most classical methods. However, experimental results show that it stays within a practical range.

Presents an algorithm that uses partitioning and gluing to compress large triangular meshes which are too complex to fit in main memory. The algorithm is based largely on the existing mesh compression algorithms, most of which require an 'in-core' representation of the input mesh. Our solution is to partition the mesh into smaller submeshes and compress these submeshes separately using existing mesh compression techniques. Since a direct partition of the input mesh is out of question, instead we partition a simplified mesh and use the partition on the simplified model to obtain a partition on the original model. In order to recover the full connectivity, we present a simple scheme for encoding/decoding the resulting boundary structure from the mesh partition. When compressing large models with few singular vertices, a negligible portion of the compressed output is devoted to gluing information. On desktop computers, we have run experiments on models with millions of vertices, which could not be compressed using standard compression software packages, and have observed compression ratios as high as 17 to 1 using our technique.

This paper deals with vessel exploration based on computed tomography angiography. Large image sequences of the lower extremities are investigated in a clinical environment. Two different approaches for peripheral vessel diagnosis dealing with stenosis and calcification detection are introduced. The paper presents an automated vessel-tracking tool for curved planar reformation. An interactive segmentation tool for bone removal is proposed.

We describe a method to visualize the connectivity graph of a mesh using a natural embedding in 3D space. This uses a 3D shape representation that is based solely on mesh connectivity: the connectivity shape. Given a connectivity, we define its natural geometry as a smooth embedding in space with uniform edge lengths and describe efficient techniques to compute it. Our main contribution is to demonstrate that a surprising amount of geometric information is implicit in the connectivity. We also show how to generate connectivity shapes that approximate given 3D shapes. Potential applications of connectivity shapes to modeling and mesh coding are described.

Vector fields can present complex structural behavior, especially in turbulent computational fluid dynamics. The topological analysis of these data sets reduces the information, but one is usually still left with too many details for interpretation. In this paper, we present a simplification approach that removes pairs of critical points from the data set, based on relevance measures. In contrast to earlier methods, no grid changes are necessary, since the whole method uses small local changes of the vector values defining the vector field. An interpretation in terms of bifurcations underlines the continuous, natural flavor of the algorithm.

We present a generic method for rapid flight planning, virtual navigation and effective camera control in a volumetric environment. Directly derived from an accurate distance from boundary (DFB) field, our automatic path planning algorithm rapidly generates centered flight paths, a skeleton, in the navigable region of the virtual environment. Based on precomputed flight paths and the DFB field, our dual-mode physically based camera control model supports a smooth, safe, and sticking-free virtual navigation with six degrees of freedom. By using these techniques, combined with accelerated volume rendering, we have successfully developed a real-time virtual colonoscopy system on low-cost PCs and confirmed the high speed, high accuracy and robustness of our techniques on more than 40 patient datasets.

Front-projection display environments suffer from a fundamental problem: users and other objects in the environment can easily and inadvertently block projectors, creating shadows on the displayed image. We introduce a technique that detects and corrects transient shadows in a multi-projector display. Our approach is to minimize the difference between predicted (generated) and observed (camera) images by continuous modification of the projected image values for each display device. We are unaware of any other technique that directly addresses this problem. Furthermore, we speculate that the general predictive monitoring framework introduced here is capable of addressing more general radiometric consistency problems such as display-surface inter-reflections and the changes in display color and intensity due to projector bulb temperature variation.Using an automatically-derived relative position of cameras and projectors in the display environment and a straightforward color correction scheme, the system renders an expected image for each camera location. Cameras observe the displayed image, which is compared with the expected image to detect shadowed regions. These regions are transformed to the appropriate projector frames, where corresponding pixel values are increased. In display regions where more than one projector contributes to the image, shadow regions are eliminated. We demonstrate an implementation of the technique to remove shadows in a multi-projector front projection system.

The growing availability of massive polygonal models, and the inability of most existing visualization tools to work with such data, has created a pressing need for memory efficient methods capable of simplifying very large meshes. In this paper, we present a method for performing adaptive simplification of polygonal meshes that are too large to fit in-core.Our algorithm performs two passes over an input mesh. In the first pass, the model is quantized using a uniform grid, and surface information is accumulated in the form of quadrics and dual quadrics. This sampling is then used to construct a BSP-Tree in which the partitioning planes are determined by the dual quadrics. In the final pass, the original vertices are clustered using the BSP-Tree, yielding an adaptive approximation of the original mesh. The BSP-Tree describes a natural simplification hierarchy, making it possible to generate a progressive transmission and construct level-of-detail representations. In this way, the algorithm provides some of the features associated with more expensive edge contraction methods while maintaining greater computational efficiency. In addition to performing adaptive simplification, our algorithm exhibits output-sensitive memory requirements and allows fine control over the size of the simplified mesh.

The visualization of scalar functions of two variables is a classic and ubiquitous application. We present a new method to visualize such data. The method is based on a non-linear mapping of the function to a height field, followed by visualization as a shaded mountain landscape. The method is easy to implement and efficient, and leads to intriguing and insightful images: The visualization is enriched by adding ridges. Three types of applications are discussed: visualization of iso-levels, clusters (multivariate data visualization), and dense contours (flow visualization).

In this paper we present a novel framework for direct volume rendering using a splatting approach based on elliptical Gaussian kernels. To avoid aliasing artifacts, we introduce the concept of a resampling filter combining a reconstruction with a low-pass kernel. Because of the similarity to Heckbert's EWA (elliptical weighted average) filter for texture mapping we call our technique EWA volume splatting. It provides high image quality without aliasing artifacts or excessive blurring even with non-spherical kernels. Hence it is suitable for regular, rectilinear, and irregular volume data sets. Moreover, our framework introduces a novel approach to compute the footprint function. It facilitates efficient perspective projection of arbitrary elliptical kernels at very little additional cost. Finally, we show that EWA volume reconstruction kernels can be reduced to surface reconstruction kernels. This makes our splat primitive universal in reconstructing surface and volume data.

Automatic detection of meaningful isosurfaces is important for producing informative visualizations of volume data, especially when no information about the data origin and imaging protocol is available. We propose a computationally efficient method for the automated detection of intensity transitions in volume data. In this approach, the dominant transitions correspond to clear maxima in cumulative Laplacian-weighted gray value histograms. Only one pass through the data volume is required to compute the histogram. Several other features which may be useful for exploration of data of unknown origin can be efficiently computed in a similar manner. The detected intensity transitions can be used for setting of visualization parameters for surface rendering, as well as for direct volume rendering of 3D datasets. When using surface rendering, the detected dominant intensity transition values correspond to the optimal surface isovalues for extraction of boundaries of the objects of interest. In direct volume rendering, such transitions are important for generation of the transfer functions, which are used to assign visualization properties to data voxels and determine the appearance of the rendered image. The proposed method is illustrated by examples with synthetic data as well as real biomedical datasets.

We present a new algorithm for extracting adaptive multiresolution triangle meshes from volume datasets. The algorithm guarantees that the topological genus of the generated mesh is the same as the genus of the surface embedded in the volume dataset at all levels of detail. In addition to this "hard constraint" on the genus of the mesh, the user can choose to specify some number of soft geometric constraints, such as triangle aspect ratio, minimum or maximum total number of vertices, minimum and/or maximum triangle edge lengths, maximum magnitude of various error metrics per triangle or vertex, including maximum curvature (area) error, maximum distance to the surface, and others. The mesh extraction process is fully automatic and does not require manual adjusting of parameters to produce the desired results as long as the user does not specify incompatible constraints. The algorithm robustly handles special topological cases, such as trimmed surfaces (intersections of the surface with the volume boundary), and manifolds with multiple disconnected components (several closed surfaces embedded in the same volume dataset). The meshes may self-intersect at coarse resolutions. However, the self-intersections are corrected automatically as the resolution of the meshes increase. We show several examples of meshes extracted from complex volume datasets.

We introduce a new algorithm for fitting a Catmull-Clark subdivision surface to a given shape within a prescribed tolerance, based on the method of quasi-interpolation. The fitting algorithm is fast, local and scales well since it does not require the solution of linear systems. Its convergence rate is optimal for regular meshes and our experiments show that it behaves very well for irregular meshes. We demonstrate the power and versatility of our method with examples from interactive modeling, surface fitting, and scientific visualization.

Brain imaging methods used in experimental brain research such as Positron Emission Tomography (PET) and Functional Magnetic Resonance (fMRI) require the analysis of large amounts of data. Exploratory statistical methods can be used to generate new hypotheses and to provide a reliable measure of a given effect. Typically, researchers report their findings by listing those regions which show significant statistical activity in a group of subjects under some experimental condition or task. A number of methods create statistical parametric maps (SPMs) of the brain on a voxel-basis. In our approach statistics are computed not on individual voxels but on predefined anatomical regions-of-interest (ROIs). A correlation coefficient is used to quantify similarity in response for various regions during an experimental setting. Since the functional inter-relationships can become rather complex and spatially widespread, they are best understood in the context of the underlying 3-D brain anatomy. However despite the power of the 3-D model, the relative location of ROIs in 3-D can be obscured due the inherent problem of presenting 3-D spatial information on a 2-D screen. In order to address this problem, we have explored a number of visualization techniques to aid the brain researcher in exploring the spatial relationships of brain activity. In this paper we present a novel 3-D interface that allows the interactive exploration of correlation datasets.

In this paper we address the problem of interactively resampling unstructured grids. Three algorithms are presented. They all allow adaptive resampling of an unstructured grid on a multiresolution hierarchy of arbitrarily sized cartesian grids according to a varying element size. Two of the algorithms presented take advantage of hardware accelerated polygon rendering and 2D texture mapping. In exploiting new features of modem PC graphics adapters, the first algorithm tries to significantly minimize the number of polygons to be rendered. Reducing rasterization requirements is the main goal of the second algorithm, which distributes the computational workload differently between the main processor and the graphics chip. By comparing them to a new pure software approach, an optimal software-hardware balance is studied. We end up with a hybrid approach which greatly improves the performance of hardware assisted resampling by involving the main processor to a higher degree and thus enabling resampling at nearly interactive rates.

Multi-resolution hierarchies of polygons and more recently of points are familiar and useful tools for achieving interactive rendering rates. We present an algorithm for tightly integrating the two into a single hierarchical data structure. The trade-off between rendering portions of a model with points or with polygons is made automatically. Our approach to this problem is to apply a bottom-up simplification process involving not only polygon simplification operations, but point replacement and point simplification operations as well. Given one or more surface meshes, our algorithm produces a hybrid hierarchy comprising both polygon and point primitives. This hierarchy may be optimized according to the relative performance characteristics of these primitive types on the intended rendering platform. We also provide a range of aggressiveness for performing point replacement operations. The most conservative approach produces a hierarchy that is better than a purely polygonal hierarchy in some places, and roughly equal in others. A less conservative approach can trade reduced complexity at the far viewing ranges for some increased complexity at the near viewing ranges. We demonstrate our approach on a number of input models, achieving primitive counts that are 1.3 to 4.7 times smaller than those of triangle-only simplification.