IEEE VIS Publication Dataset

A similarity metric based on the low-level content of images can be used to create a visualisation in which visually similar images are displayed close to each other. We are carrying out a series of experiments to evaluate the usefulness of this type of visualisation as an image browsing aid. The initial experiment, described, considered whether people would find a given photograph more quickly in a visualisation than in a randomly arranged grid of images. The results show that the subjects were faster with the visualisation, although in post-experiment interviews many of them said that they preferred the clarity and regularity of the grid. We describe an algorithm with which the best aspects of the two layout types can be combined

Interactive selection is a critical component in exploratory visualization, allowing users to isolate subsets of the displayed information for highlighting, deleting, analysis, or focussed investigation. Brushing, a popular method for implementing the selection process, has traditionally been performed in either screen space or data space. We introduce the concept of a structure-based brush, which can be used to perform selection in hierarchically structured data sets. Our structure-based brush allows users to navigate hierarchies by specifying focal extents and level-of-detail on a visual representation of the structure. Proximity-based coloring, which maps similar colors to data that are closely related within the structure, helps convey both structural relationships and anomalies. We describe the design and implementation of our structure-based brushing tool. We also validate its usefulness using two distinct hierarchical visualization techniques, namely hierarchical parallel coordinates and tree-maps

In the process of knowledge discovery, workers examine available information in order to make sense of it. By sensemaking, we mean interacting with and operating on the information with a variety of information processing mechanisms. Previously, we introduced a concept that uses the spreadsheet metaphor with cells containing visualizations of complex data. We extend and apply a cognitive model called “visual sensemaking” to the visualization spreadsheet. We use the task of making sense of a large Web site as a concrete example throughout the paper for demonstration. Using a variety of visualization techniques, such as the Disk Tree and Cone Tree, we show that the interactions of the visualization spreadsheet help users draw conclusions from the overall relationships of the entire information set

Automation has arrived to parallel coordinates. A geometrically motivated classifier is presented and applied, with both training and testing stages, to 3 real datasets. Our results compared to those from 33 other classifiers have the least error. The algorithm is based on parallel coordinates and has very low computational complexity in the number of variables and the size of the dataset-contrasted with the very high or unknown (often unstated) complexity of other classifiers, the low complexity enables the rule derivation to be done in near real-time hence making the classification adaptive to changing conditions, provides comprehensible and explicit rules-contrasted to neural networks which are “black boxes”, does dimensionality selection-where the minimal set of original variables (not transformed new variables as in Principal Component Analysis) required to state the rule is found, orders these variables so as to optimize the clarity of separation between the designated set and its complement-this solves the pesky “ordering problem” in parallel coordinates. The algorithm is display independent, hence it can be applied to very large in size and number of variables datasets. Though it is instructive to present the results visually, the input size is no longer display-limited as for visual data mining

This paper introduces the Sunflower visual metaphor for information visualization. The visual metaphor is presented as an alternative to current techniques of dimensional compression and the visualization tools that employ them. The paper discusses the motivation for the Sunflower paradigm, its implementation and critical factors for producing an effective visualization. A primary driver in this research effort has been to develop a visualization tool that facilitates browsing, knowledge discovery, and that supports learning through sense making and integration of new information

VisageWeb is an information-centric user interface to the World Wide Web built within the Visage data visualization environment. This paper traces the development of the VisageWeb project, using it to motivate an exploration of how an information-centric architecture copes with new visualization challenges. We conclude with a presentation of the VisageWeb prototype itself

The advent of superscalar processors with out-of-order execution makes it increasingly difficult to determine how well an application is utilizing the processor and how to adapt the application to improve its performance. We describe a visualization system for the analysis of application behavior on superscalar processors. Our system provides an overview-plus-detail display of the application's execution. A timeline view of pipeline performance data shows the overall utilization of the pipeline. This information is displayed using multiple time scales, enabling the user to drill down from a high-level application overview to a focus region of hundreds of cycles. This region of interest is displayed in detail using an animated cycle-by-cycle view of the execution. This view shows how instructions are reordered and executed and how functional units are being utilized. Additional context views correlate instuctions in this detailed view with the relevant source code for the application. This allows the user to discover the root cause of the poor pipeline utilization and make changes to the application to improve its performance. This visualization system can be easily configured to display a variety of processor models and configurations. We demonstrate it for both the MXS and MMIX processor models

An association rule in data mining is an implication of the form X→Y where X is a set of antecedent items and Y is the consequent item. For years researchers have developed many tools to visualize association rules. However, few of these tools can handle more than dozens of rules, and none of them can effectively manage rules with multiple antecedents. Thus, it is extremely difficult to visualize and understand the association information of a large data set even when all the rules are available. This paper presents a novel visualization technique to tackle many of these problems. We apply the technology to a text mining study on large corpora. The results indicate that our design can easily handle hundreds of multiple antecedent association rules in a three-dimensional display with minimum human interaction, low occlusion percentage, and no screen swapping

The molecular events involved in the activation of G protein-coupled receptors, represent a fundamental biochemical process. These events were selected for animation because the mechanism involves both a ligand-receptor conformational shape change, and an enzyme-substrate conformational shape change. Expository animation brought this biochemical process to life.

Recent interest in large displays has led to renewed development of tiled displays, which are comprised of several individual displays arranged in an array and used as one large logical display. Stanford's "Interactive Mural" is an example of such a display, using an overlapping four by two array of projectors that back-project onto a diffuse screen to form a 6' by 2' display area with a resolution of over 60 dpi. Writing software to make effective use of the large display space is a challenge because normal window system interaction metaphors break down. One promising approach is to switch to immersive applications; another approach, the one we are investigating, is to emulate office, conference room or studio environments which use the space to display a collection of visual material to support group activities. We describe a virtual graphics system that is designed to support multiple simultaneous rendering streams from both local and remote sites. The system abstracts the physical number of computers, graphics subsystems and projectors used to create the display. We provide performance measurements to show that the system scales well and thus supports a variety of different hardware configurations. The system is also interesting because it uses transparent "layers", instead of windows, to manage the screen.

We present a fast volume rendering algorithm for time-varying fields. We propose a new data structure, called time-space partitioning (TSP) tree, that can effectively capture both the spatial and the temporal coherence from a time-varying field. Using the proposed data structure, the rendering speed is substantially improved. In addition, our data structure helps to maintain the memory access locality and to provide the sparse data traversal so that our algorithm becomes suitable for large-scale out-of-core applications. Finally, our algorithm allows flexible error control for both the temporal and the spatial coherence so that a trade-off between image quality and rendering speed is possible. We demonstrate the utility and speed of our algorithm with data from several time-varying CFD simulations. Our rendering algorithm can achieve substantial speedup while the storage space overhead for the TSP tree is kept at a minimum.

We approach the problem of exploring a virtual space by exploiting positional and camera-model constraints on navigation to provide extra assistance that focuses the user's explorational wanderings on the task objectives. Our specific design incorporates not only task-based constraints on the viewer's location, gaze, and viewing parameters, but also a personal "glide" that serves two important functions: keeping the user oriented in the navigation space, and "pointing" to interesting subject areas as they are approached. The guide's cues may be ignored by continuing in motion, but if the user stops, the gaze shifts automatically toward whatever the guide was interested in. This design has the serendipitous feature that it automatically incorporates a nested collaborative paradigm simply by allowing any given viewer to be seen as the "guide" of one or more viewers following behind; the leading automated guide (we tend to select a guide dog for this avatar) can remind the leading live human guide of interesting sites to point out, while each real human collaborator down the chain has some choices about whether to follow the local leader's hints. We have chosen VRML as our initial development medium primarily because of its portability, and we have implemented a variety of natural modes for leading and collaborating, including ways for collaborators to attach to and detach from a particular leader.

Computer simulation and digital measuring systems are now generating data of unprecedented size. The size of data is becoming so large that conventional visualization tools are incapable of processing it, which is in turn is impacting the effectiveness of computational tools. In this paper we describe an object-oriented architecture that addresses this problem by automatically breaking data into pieces, and then processes the data piece-by-piece within a pipeline of filters. The piece size is user specified and can be controlled to eliminate the need for swapping (i.e., relying on virtual memory). In addition, because piece size can be controlled, any size problem can be run on any size computer, at the expense of extra computational time. Furthermore pieces are automatically broken into sub-pieces and each piece assigned to a different thread for parallel processing. This paper includes numerical performance studies and references to the source code which is freely available on the Web.

Many volume filtering operations used for image enhancement, data processing or feature detection can be written in terms of three-dimensional convolutions. It is not possible to yield interactive frame rates on todays hardware when applying such convolutions on volume data using software filter routines. As modern graphics workstations have the ability to render two-dimensional convoluted images to the frame buffer, this feature can be used to accelerate the process significantly. This way generic 3D convolution can be added as a powerful tool in interactive volume visualization toolkits.

Analyzing options is a complex, multi-variate process. Option behavior depends on a variety of market conditions which vary over the time course of the option. The goal of this project is to provide an interactive visual environment which allows the analyst to explore these complex interactions, and to select and construct specific views for communicating information to non-analysts (e.g., marketing managers and customers). In this paper we describe an environment for exploring 2- and 3-dimensional representations of options data, dynamically varying parameters, examining how multi-variate relationships develop over time, and exploring the likelihood of the development of different outcomes over the life of the option. We also demonstrate how this tool has been used by analysts to communicate to non-analysts how particular options no longer deliver the behavior they were originally intended to provide.

This paper describes a method to simulate realistic wrinkles on clothes without fine mesh and large computational overheads. Cloth has very little in-plane deformations, as most of the deformations come from buckling. This can be looked at as area conservation property of cloth. The area conservation formulation of the method modulates the user defined wrinkle pattern, based on deformation of individual triangle. The methodology facilitates use of small in-plane deformation stiffnesses and a coarse mesh for the numerical simulation, this makes cloth simulation fast and robust. Moreover, the ability to design wrinkles (even on generalized deformable models) makes this method versatile for synthetic image generation. The method inspired from cloth wrinkling problem, being geometric in nature, can be extended to other wrinkling phenomena.

Vector field visualization is an important topic in scientific visualization. Its aim is to graphically represent field data in an intuitively understandable and precise way. Here a new approach based on anisotropic nonlinear diffusion is introduced. It enables an easy perception of flow data and serves as an appropriate scale space method for the visualization of complicated flow patterns. The approach is closely related to nonlinear diffusion methods in image analysis where images are smoothed while still retaining and enhancing edges. An initial noisy image is smoothed along streamlines, whereas the image is sharpened in the orthogonal direction. The method is based on a continuous model and requires the solution of a parabolic PDE problem. It is discretized only in the final implementational step. Therefore, many important qualitative aspects can already be discussed on a continuous level. Applications are shown in 2D and 3D and the provisions for flow segmentation are outlined.

This paper describes initial results of a 3D field topology analysis for automating transfer function design aiming at comprehensible volume rendering. The conventional Reeb graph-based approach to describing topological features of 3D surfaces is extended to capture the topological skeleton of a volumetric field. Based on the analysis result, which is represented in the form of a hyper Reeb graph, a procedure is proposed for designing appropriate color/opacity transfer functions. Two analytic volume datasets are used to preliminarily prove the feasibility of the present design methodology.

An application of C 1 scalar interpolation for 2D vector field topology visualization is presented. Powell-Sabin and Nielson interpolants are considered which both make use of Nielson's Minimum Norm Network for the precomputation of the derivatives in our implementation. A comparison of their results to the commonly used linear interpolant underlines their significant improvement of singularity location and topological skeleton depiction. Evaluation is based upon the processing of polynomial vector fields with known topology containing higher order singularities.