IEEE VIS Publication Dataset

In this paper the motivation, design and application of a distributed blackboard architecture for interactive data visualization is discussed. The main advantages of the architecture are twofold. First, it allows visualization tools to be tightly integrated with simulations. Second, it allows qualitative and quantitative analysis to be combined during the visualization process.

Many sophisticated solutions have been proposed to reduce the geometric complexity of 3D meshes. A problem studied less often is how to preserve on a simplified mesh the detail (e.g., color, high frequency shape detail, scalar fields, etc.) which is encoded in the original mesh. We present a general approach for preserving detail on simplified meshes. The detail (or high frequency information) lost after simplification is encoded through texture or bump maps. The original contribution is that preservation is performed after simplification, by building set of triangular texture patches that are then packed in a single texture map. Each simplified mesh face is sampled to build the associated triangular texture patch; a new method for storing this set of texture patches into a standard rectangular texture is presented and discussed. Our detail preserving approach makes no assumptions about the simplification process adopted to reduce mesh complexity and allows highly efficient rendering. The solution is very general, allowing preservation of any attribute value defined on the high resolution mesh. We also describe an alternative application: the conversion of 3D models with 3D static procedural textures into standard 3D models with 2D textures.

This paper presents a novel method to extract vortical structures from 3D CFD (computational fluid dynamics) vector fields automatically. It discusses the underlying theory and some aspects of the implementation. Making use of higher-order derivatives, the method is able to locate bent vortices. In order to structure the recognition procedure, we distinguish locating the core line from calculating attributes of strength and quality. Results are presented on several flow fields from the field of turbomachinery.

We present a new approach for simplifying models composed of polygons or spline patches. Given an input model, the algorithm computes a new representation of the model in terms of triangular Bezier patches. It performs a series of geometric operations, consisting of patch merging and swapping diagonals, and makes use of batch connectivity information to generate C-LODs (curved levels-of-detail). Each C-LOD is represented using cubic triangular Bezier patches. The C-LODs provide a compact representation for storing the model. The algorithm tries to minimize the surface deviation error and maintains continuity at patch boundaries. Given the CLODs, the algorithm can generate their polygonal approximations using static and dynamic tessellation schemes. It has been implemented and we highlight its performance on a number of polygonal and spline models.

We present an efficient and robust ray-casting algorithm for directly rendering a curvilinear volume of arbitrarily-shaped cells. We designed the algorithm to alleviate the consumption of CPU power and memory space. By incorporating the essence of the projection paradigm into the ray-casting process, we have successfully accelerated the ray traversal through the grid and data interpolations at sample points. Our algorithm also overcomes the conventional limitation requiring the cells to be convex. Application of this algorithm to several commonly-used curvilinear data sets has produced a favorable performance when compared with recently reported algorithms.

Visualization and quantification methods are being developed to analyze our acoustic images of thermal plumes containing metallic mineral particles that discharge from hot springs on the deep seafloor. The acoustic images record intensity of backscattering from the particulate matter suspended in the plumes. The visualization methods extract, classify, visualize, measure and track reconstructions of the plumes, depicted by isointensity surfaces as 3D volume objects and 2D slices. The parameters measured, including plume volume, cross sectional area, centerline location (trajectory), surface area and isosurfaces at percentages of maximum backscatter intensity, are being used to derive elements of plume behavior including expansion with height, dilution, and mechanisms of entrainment of surrounding seawater. Our aim is to compare the observational data with predictions of plume theory to test and advance models of the behavior of hydrothermal plumes through the use of multiple representations.

A fully automatic feature detection algorithm is presented that locates and distinguishes lines of flow separation and attachment on surfaces in 3D numerical flow fields. The algorithm is based on concepts from 2D phase-plane analysis of linear vector fields. Unlike prior visualization techniques based on particle tracing or flow topology, the phase-plane algorithm detects separation using local analytic tests. The results show that it not only detects the standard closed separation lines but also the illusive open separation lines which are not captured by flow topology methods.

In this paper we describe a battlefield visualization system, called Dragon, which we have implemented on a virtual reality responsive workbench. The Dragon system has been successfully deployed as part of two large military exercises: the Hunter Warrior advanced warfighting experiment, in March 1997, and the Joint Counter Mine advanced concept tactical demonstration, in August and September 1997. We describe battlefield visualization, the Dragon system, and the workbench, and we describe our experiences as part of these two real-world deployments, with an emphasis on lessons learned and needed future work.

Presents a new method for using texture to visualize multi-dimensional data elements arranged on an underlying 3D height field. We hope to use simple texture patterns in combination with other visual features like hue and intensity to increase the number of attribute values we can display simultaneously. Our technique builds perceptual texture elements (or pexels) to represent each data element. Attribute values encoded in the data element are used to vary the appearance of a corresponding pexel. Texture patterns that form when the pexels are displayed can be used to rapidly and accurately explore the dataset. Our pexels are built by controlling three separate texture dimensions: height, density and regularity. Results from computer graphics, computer vision and cognitive psychology have identified these dimensions as important for the formation of perceptual texture patterns. We conducted a set of controlled experiments to measure the effectiveness of these dimensions, and to identify any visual interference that may occur when all three are displayed simultaneously at the same spatial location. Results from our experiments show that these dimensions can be used in specific combinations to form perceptual textures for visualizing multidimensional datasets. We demonstrate the effectiveness of our technique by applying it to two real-world visualization environments: tracking typhoon activity in southeast Asia, and analyzing ocean conditions in the northern Pacific.

Spot noise and line integral convolution (LIC) are two texture synthesis techniques for vector field visualization. The two techniques are compared. Continuous directional convolution is used as a common basis for comparing the techniques. It is shown that the techniques are based on the same mathematical concept. Comparisons of the visual appearance of the output and performance of the algorithms are made.

We are studying difficult geometric problems in computer-aided mechanical design where visualization plays a key role. The research addresses the fundamental design task of contact analysis: deriving the part contacts and the ensuing motion constraints in a mechanical system. We have automated contact analysis of general planar systems via configuration space computation. Configuration space is a geometric representation of rigid-body interaction that encodes quantitative information, such as part motion paths, and qualitative information, such as system failure modes. The configuration space dimension equals the number of degrees of freedom in the system. Three-dimensional spaces are most important, but higher-dimensions are often useful. The qualitative aspects, which relate to the topology of the configuration space, are best understood by visualization. We explain what configuration space is, how it encodes contact information, and what research challenges it poses for visualization.

We propose a general paradigm for computing optimal coordinate frame fields that may be exploited to visualize curves and surfaces. Parallel transport framings, which work well for open curves, generally fail to have desirable properties for cyclic curves and for surfaces. We suggest that minimal quaternion measure provides an appropriate heuristic generalization of parallel transport. Our approach differs from minimal tangential acceleration approaches due to the addition of "sliding ring" constraints that fix one frame axis, but allow an axial rotational freedom whose value is varied in the optimization process. Our fundamental tool is the quaternion Gauss map, a generalization to quaternion space of the tangent map for curves and of the Gauss map for surfaces. The quaternion Gauss map takes 3D coordinate frame fields for curves and surfaces into corresponding curves and surfaces constrained to the space of possible orientations in quaternion space. Standard optimization tools provide application specific means of choosing optimal, e.g., length- or area-minimizing, quaternion frame fields in this constrained space.

Area cartograms are used for visualizing geographically distributed data by attaching measurements to regions of a map and scaling the regions such that their areas are proportional to the measured quantities. A continuous area cartogram is a cartogram that is constructed without changing the underlying map topology. We present a new algorithm for the construction of continuous area cartograms that was developed by viewing their construction as a constrained optimization problem. The algorithm uses a relaxation method that exploits hierarchical resolution, constrained dynamics, and a scheme that alternates goals of achieving correct region areas and adjusting region shapes. It is compared favorably to existing methods in its ability to preserve region shape recognition cues, while still achieving high accuracy.

Interpolating contours and reconstructing a rational surface from a contour map are two essential problems in terrain modeling. They are often met in the field of computer graphics and CAD systems based on geographic information systems. Although many approaches have been developed for these two problems, one difficulty still remains. That is how to ensure that the reconstructed surface is both smooth globally and coincides with the given contours exactly simultaneously. In this paper we solve the two problems in a unified framework. We use gradient controlled partial differential equation (PDE) surfaces to express terrain surfaces, in which the surface shapes can be globally determined by the contours, their locations, height and gradient values. The surface generated by this method is accurate in the sense of exactly coinciding with the original contours and smooth with C1 continuity everywhere. The method can reveal smooth saddle shapes caused by surface branching of one to more and can make rational interpolated sub-contours between two or more neighboring contours.

Many real world polygonal surfaces contain topological singularities that represent a challenge for processes such as simplification, compression, smoothing, etc. We present an algorithm for removing such singularities, thus converting non manifold sets of polygons to manifold polygonal surfaces (orientable if necessary). We identify singular vertices and edges, multiply singular vertices, and cut through singular edges. In an optional stitching phase, we join surface boundary edges that were cut, or whose endpoints are sufficiently close, while guaranteeing that the surface is a manifold. We study two different stitching strategies called "edge pinching" and "edge snapping"; when snapping, special care is required to avoid re-creating singularities. The algorithm manipulates the polygon vertex indices (surface topology) and essentially ignores vertex coordinates (surface geometry). Except for the optional stitching, the algorithm has a linear complexity in the number of vertices edges and faces, and require no floating point operation.

The paper describes the architecture of a data level comparative visualization system and experiences using it to study computational fluid dynamics data and experimental wind tunnel data. We illustrate how the system can be used to compare data sets from different sources, data sets with different resolutions and data sets computed using different mathematical models of fluid flow. Suggested improvements to the system based on user feedback are also discussed.

This case study describes the design and development of VISOR (Visual Integration of Simulated and Observed Results), a tool which supports the visualization and analysis of a wide variety of data relevant to aerospace engineering design. Integrating data from such disparate sources is challenging; overcoming the obstacles results in a powerful tool. The process has also been valuable in exposing requirements for the libraries of reusable software tools for visualization and data analysis being developed at NASA Ames.

Presents an efficient algorithm for the reconstruction of a multivariate function from multiple sets of scattered data. Given N sets of scattered data representing N distinct dependent variables that have been sampled independently over a common domain and N error tolerance values, the algorithm constructs a triangulation of the domain of the data and associates multivariate values with the vertices of the triangulation. The resulting linear interpolation of these multivariate values yields a multivariate function, called a co-triangulation, that represents all of the dependent data up to the given error tolerance. A simple iterative algorithm for the construction of a co-triangulation from any number of data sets is presented and analyzed. The main contribution of this paper lies in the description of a highly efficient framework for the realization of this approximation algorithm. While the asymptotic time complexity of the algorithm certainly remains within the theoretical bounds, we demonstrate that it is possible to achieve running times that depend only linearly on the number of data even for very large problems with more than two million samples. This efficient realization of the algorithm uses adapted dynamic data structures and careful caching in an integrated framework.

Multi-triangulation (MT) is a general framework for managing the level-of-detail in large triangle meshes, which we have introduced in our previous work. In this paper, we describe an efficient implementation of an MT based on vertex decimation. We present general techniques for querying an MT, which are independent of a specific application, and which can be applied for solving problems, such as selective refinement, windowing, point location, and other spatial interference queries. We describe alternative data structures for encoding an MT, which achieve different trade-offs between space and performance. Experimental results are discussed.