IEEE VIS Publication Dataset

The authors consider the multi-triangulation, a general model for representing surfaces at variable resolution based on triangle meshes. They analyse characteristics of the model that make it effective for supporting basic operations such as extraction of a surface approximation, and point location. An interruptible algorithm for extracting a representation at a resolution variable over the surface is presented. Different heuristics for building the model are considered and compared. Results on both the construction and the extraction algorithm are presented.

Numerical finite element simulations of the behaviour of a car body in frontal, side or rear impact collision scenarios have become increasingly complex as well as reliable and precise. They are well-established as a standard evaluation tool in the automotive development process. Both the increased complexity and the advances in computer graphics technology have resulted in the need for new visualization techniques to facilitate the analysis of the immense amount of data originating from such scientific engineering computations. Expanding the effectiveness of traditional post-processing techniques is one key to achieve shorter design cycles and faster time-to-market. In this paper, we describe how the extensive use of texture mapping and new visualization mappings like force tubing can considerably enhance the post-processing of structural and physical properties of car components in crash simulations. We show that, using these techniques, both the calculation costs and the rendering costs are reduced, and the quality of the visualization is improved.

We describe a set of visualization programs developed for understanding segmentations of customer records produced by a self organizing map (SOM) algorithm. A SOM produces segments of similar customer records that can then be used as the basis of a marketing campaign. Since the characteristics that each segment will have in common are not specified a priori, visualization is essential to understanding the segment to design specific marketing strategies. Two different styles of visualizations were found to be useful for the two types of observers of the data. Abstract overviews of the entire segmentation were designed for analysts applying the SOM algorithm. Detailed scatterplots of individual records were designed for communicating the results to decision makers specifying marketing strategy.

The ability to forecast the progress of crisis events would significantly reduce human suffering and loss of life, the destruction of property and expenditures for assessment and recovery. Los Alamos National Laboratory has established a scientific thrust in crisis forecasting to address this national challenge. In the initial phase of this project, scientists at Los Alamos are developing computer models to predict the spread of a wildfire. Visualization of the results of the wildfire simulation will be used by scientists to assess the quality of the simulation and eventually by fire personnel as a visual forecast of the wildfire's evolution. The fire personnel and scientists want the visualization to look as realistic as possible without compromising scientific accuracy. This paper describes how the visualization was created, analyzes the tools and approach that were used, and suggests directions for future work and research.

The paper discusses CAVEvis and a related set of tools for the interactive visualization and exploration of large sets of time-varying scalar and vector fields using the CAVE virtual reality environment. Since visualization of large data sets can be very time-consuming in both computation and rendering time, the task is distributed over multiple machines, each of which is specialized for some aspect of the visualization process. All modules must run asynchronously to maintain the highest level of interactivity. A model of distributed visualization is introduced that addresses important issues related to the management of time-dependent data, module synchronization, and interactivity bottlenecks.

We present collaborative scientific visualization in STUDIERSTUBE. STUDIERSTUBE is an augmented reality system that has several advantages over conventional desktop and other virtual reality environments, including true stereoscopy, 3D-interaction, individual viewpoints and customized views for multiple users, unhindered natural collaboration and low cost. We demonstrate the application of this concept for the interaction of multiple users and illustrate it with several visualizations of dynamical systems in DynSys3D, a visualization system running on top of AVS.

Current visualization systems are designed around a single user model, making it awkward for large research teams to collectively analyse large data sets. The paper shows how the popular data flow approach to visualization can be extended to allow multiple users to collaborate-each running their own visualization pipeline but with the opportunity to connect in data generated by a colleague, Thus collaborative visualizations are 'programmed' in exactly the same 'plug-and-play' style as is now customary for single-user mode. The paper describes a system architecture that can act as a basis for the collaborative extension of any data flow visualization system, and the ideas are demonstrated through a particular implementation in terms of IRIS Explorer.

We propose a probability model for the handling of complicated interactions between volumetric objects. In our model each volume is associated with a "probability map" that assigns a "surface crossing" probability to each space point according to local volume properties. The interaction between two volumes is then described by finding the intersecting regions between the volumes, and calculating the "collision probabilities" at each intersecting point from the surface crossing probabilities. To enable fast and efficient calculations, we introduce the concept of a distance map and develop two hierarchical collision detection algorithms, taking advantage of the uniform structure of volumetric datasets.

An algorithm for computing a triangulated surface which separates a collection of data points that have been segmented into a number of different classes is presented. The problem generalizes the concept of an isosurface which separates data points that have been segmented into only two classes: those for which data function values are above the threshold and those which are below the threshold value. The algorithm is very simple, easy to implement and applies without limit to the number of classes.

Navigation through 3D spaces is required in many interactive graphics and virtual reality applications. The authors consider the subclass of situations in which a 2D device such as a mouse controls smooth movements among viewpoints for a "through the screen" display of a 3D world. Frequently, there is a poor match between the goal of such a navigation activity, the control device, and the skills of the average user. They propose a unified mathematical framework for incorporating context-dependent constraints into the generalized viewpoint generation problem. These designer-supplied constraint modes provide a middle ground between the triviality of a single camera animation path and the confusing excess freedom of common unconstrained control paradigms. They illustrate the approach with a variety of examples, including terrain models, interior architectural spaces, and complex molecules.

Genus-reducing simplifications are important in constructing multiresolution hierarchies for level-of-detail-based rendering, especially for datasets that have several relatively small holes, tunnels, and cavities. We present a genus-reducing simplification approach that is complementary to the existing work on genus-preserving simplifications. We propose a simplification framework in which genus-reducing and genus-preserving simplifications alternate to yield much better multiresolution hierarchies than would have been possible by using either one of them. In our approach we first identify the holes and the concavities by extending the concept of α-hulls to polygonal meshes under the L ∞ distance metric and then generate valid triangulations to fill them.

Climatological data about thunderstorms is traditionally collected by balloons or planes traveling through the storm along straight tracts. Such data lends itself to simple 2D representations. The data described in this paper was gathered by a sail plane spiraling in an updraft within a thundercloud. The more complex organization of data samples demands more complex representation methods. This paper describes a system developed using the Visualization Toolkit (VTK) to explore such data. The data consists of several scalar values and a set of vector values associated with positional data on the measuring devices. The goal of this visualization is to explore the location of point charges suggested by the electromagnetic field vectors and determine if any correlation exists between the point charge location and standard cloud microstructure scalar measurements such as temperature. There are several problems associated with visualizing this rather unique set of data. They stem from the fact that the data is a sparse spiraling sample of scalars and vectors. The system allows the track of the plane to be displayed as a line, a tube or a ribbon; scalar values can be displayed as transparent isosurfaces; and the vector data as an arrow plot along that track, given a color that is constant, based on orientation or related to the value of a scalar. Any combination of methods can be used to display the data. A single primitive can be overloaded in many ways, or several different variables can all be displayed simultaneously.

The paper introduces a tool for visualizing a multidimensional relevance space. Abstractly, the information to be displayed consists of a large number of objects, a set of features that are likely to be of interest to the user, and some function that measures the relevance level of every object to the various features. The goal is to provide the user with a concise and comprehensible visualization of that information. For the type of applications concentrated on, the exact relevance measures of the objects are not significant. This enables accuracy to be traded for a clearer display. The idea is to "flatten" the multidimensionality of the feature space into a 2D "relevance map", capturing the inter-relations among the features, without causing too many ambiguous interpretations of the results. To better reflect the nature of the data and to resolve the ambiguity the authors refine the given set of features and introduce the notion of composed features. The layout of the map is then obtained by grading it according to a set of rules and using a simulated annealing algorithm which optimizes the layout with respect to these rules. The technique proposed has been implemented and tested, in the context of visualizing the result of a Web search, in the RMAP (Relevance Map) prototype system.

Describes data exploration techniques designed to classify DNA sequences. Several visualization and data mining techniques were used to validate and attempt to discover new methods for distinguishing coding DNA sequences (exons) from non-coding DNA sequences (introns). The goal of the data mining was to see whether some other, possibly non-linear combination of the fundamental position-dependent DNA nucleotide frequency values could be a better predictor than the AMI (average mutual information). We tried many different classification techniques including rule-based classifiers and neural networks. We also used visualization of both the original data and the results of the data mining to help verify patterns and to understand the distinction between the different types of data and classifications. In particular, the visualization helped us develop refinements to neural network classifiers, which have accuracies as high as any known method. Finally, we discuss the interactions between visualization and data mining and suggest an integrated approach.

Color is widely and reliably used to display the value of a single scalar variable. It is more rarely, and far less reliably, used to display multivariate data. Dynamic control over the parameters of the color mapping results in a more effective environment for the exploration of multivariate spatial distributions. The paper describes an empirical study comparing the effectiveness of static versus dynamic representations for the exploration of qualitative aspects of bivariate distributions. In this experiment, subjects made judgments about the correspondence of the shape, location, and magnitude of two patterns under conditions with varying amounts of random noise. Subjects made significantly more correct judgements (p

Recursive subdivision schemes have been extensively used in computer graphics and scientific visualization for modeling smooth surfaces of arbitrary topology. Recursive subdivision generates a visually pleasing smooth surface in the limit from an initial user-specified polygonal mesh through the repeated application of a fixed set of subdivision rules. In this paper, we present a new dynamic surface model based on the Catmull-Clark (1978) subdivision scheme, which is a very popular method to model complicated objects of arbitrary genus because of many of its nice properties. Our new dynamic surface model inherits the attractive properties of the Catmull-Clark subdivision scheme as well as that of the physics-based modeling paradigm. This new model provides a direct and intuitive means of manipulating geometric shapes, a fast, robust and hierarchical approach for recovering complex geometric shapes from range and volume data using very few degrees of freedom (control vertices). We provide an analytic formulation and introduce the physical quantities required to develop the dynamic subdivision surface model which can be interactively deformed by applying synthesized forces in real time. The governing dynamic differential equation is derived using Lagrangian mechanics and a finite element discretization. Our experiments demonstrate that this new dynamic model has a promising future in computer graphics, geometric shape design and scientific visualization.

The paper discusses the problem of subdividing unstructured mesh topologies containing hexahedra, prisms, pyramids and tetrahedra into a consistent set of only tetrahedra, while preserving the overall mesh topology. Efficient algorithms for volume rendering, iso-contouring and particle advection exist for mesh topologies comprised solely of tetrahedra. General finite-element simulations however, consist mainly of hexahedra, and possibly prisms, pyramids and tetrahedra. Arbitrary subdivision of these mesh topologies into tetrahedra can lead to discontinuous behaviour across element faces. This will show up as visible artifacts in the iso-contouring and volume rendering algorithms, and lead to impossible face adjacency graphs for many algorithms. The authors present various properties of tetrahedral subdivisions, and an algorithm SOP determining a consistent subdivision containing a minimal set of tetrahedra.

The paper discusses techniques for extracting feature lines from three-dimensional unstructured grids. The twin objectives are to facilitate the interactive manipulation of these typically very large and dense meshes, and to clarify the visualization of the solution data that accompanies them. The authors describe the perceptual importance of specific viewpoint-dependent and view-independent features, discuss the relative advantages and disadvantages of several alternative algorithms for identifying these features (taking into consideration both local and global criteria), and demonstrate the results of these methods on a variety of different data sets.

Software has been developed to apply visualization techniques to aeronautics data collected during wind tunnel experiments. Interaction between the software developers and the aeroscientists has been crucial in making the software. The interaction has also been important in building the scientists' confidence in the use of interactive, computer-mediated analysis tools.

Oriented line integral convolution (OLIC) illustrates flow fields by convolving a sparse texture with an anisotropic convolution kernel. The kernel is aligned to the underlying flow of the vector field. OLIC does not only show the direction of the flow but also its orientation. The paper presents fast rendering of oriented line integral convolution (FROLIC), which is approximately two orders of magnitude faster than OLIC. Costly convolution operations as done in OLIC are replaced in FROLIC by approximating a streamlet through a set of disks with varying intensity. The issue of overlapping streamlets is discussed. Two efficient animation techniques for animating FROLIC images are described. FROLIC has been implemented as a Java applet. This allows researchers from various disciplines (typically with inhomogenous hardware environments) to conveniently explore and investigate analytically defined 2D vector fields.