DevLan/vispubs huggingface dataset:
Using multilevel call matrices in large software projects
Authors: Frank van Ham
Published at InfoVis, 2003

Traditionally, node link diagrams are the prime choice when it comes to visualizing software architectures. However, node link diagrams often fall short when used to visualize large graph structures. In this paper we investigate the use of call matrices as visual aids in the management of large software projects. We argue that call matrices have a number of advantages over traditional node link diagrams when the main object of interest is the link instead of the node. Matrix visualizations can provide stable and crisp layouts of large graphs and are inherently well suited for large multilevel visualizations because of their recursive structure. We discuss a number of visualization issues, using a very large software project currently under development at Philips Medical Systems as a running example.
Visualization of Labeled Data Using Linear Transformation
Authors: Yehuda Koren, Liran Carmel
Published at InfoVis, 2003

We present a novel family of data-driven linear transformations, aimed at visualizing multivariate data in a low-dimensional space in a way that optimally preserves the structure of the data. The well-studied PCA and Fisher's LDA (linear discriminant analysis) are shown to be special members in this family of transformations, and we demonstrate how to generalize these two methods such as to enhance their performance. Furthermore, our technique is the only one, to the best of our knowledge, that reflects in the resulting embedding both the data coordinates and pairwise similarities and/or dissimilarities between the data elements. Even more so, when information on the clustering (labeling) decomposition of the data is known, this information can be integrated in the linear transformation, resulting in embeddings that clearly show the separation between the clusters, as well as their infrastructure. All this makes our technique very flexible and powerful, and lets us cope with kinds of data that other techniques fail to describe properly.
Visualization of large-scale customer satisfaction surveys using a parallel coordinate tree
Authors: Dominique Brodbeck, Luc Girardin
Published at InfoVis, 2003

Satisfaction surveys are an important measurement tool in fields such as market research or human resources management. Serious studies consist of numerous questions and contain answers from large population samples. Aggregation on both sides, the questions asked as well as the answers received, turns the multidimensional problem into a complex system of interleaved hierarchies. Traditional ways of presenting the results are limited to one-dimensional charts and cross-tables. We developed a visualization method called the Parallel Coordinate Tree that combines multidimensional analysis with a tree structure representation. Distortion-oriented focus+context techniques are used to facilitate interaction with the visualization. In this paper we present a design study of a commercial application that we built, using this method to analyze and communicate results from large-scale customer satisfaction surveys.
Visualizing evolving networks: minimum spanning trees versus pathfinder networks
Authors: Chaomei Chen, Steven A. Morris
Published at InfoVis, 2003

Network evolution is an ubiquitous phenomenon in a wide variety of complex systems. There is an increasing interest in statistically modeling the evolution of complex networks such as small-world networks and scale-free networks. In this article, we address a practical issue concerning the visualizations of co-citation networks of scientific publications derived by two widely known link reduction algorithms, namely minimum spanning trees (MSTs) and pathfinder networks (PFNETs). Our primary goal is to identify the strengths and weaknesses of the two methods in fulfilling the need for visualizing evolving networks. Two criteria are derived for assessing visualizations of evolving networks in terms of topological properties and dynamical properties. We examine the animated visualization models of the evolution of botulinum toxin research in terms of its co-citation structure across a 58-year span (1945-2002). The results suggest that although high-degree nodes dominate the structure of MST models, such structures can be inadequate in depicting the essence of how the network evolves because MST removes potentially significant links from high-order shortest paths. In contrast, PFNET models clearly demonstrate their superiority in maintaining the cohesiveness of some of the most pivotal paths, which in turn make the growth animation more predictable and interpretable. We suggest that the design of visualization and modeling tools for network evolution should take the cohesiveness of critical paths into account.
A Robust Level-Set Algorithm for Centerline Extraction
Authors: Alexandru C. Telea, Anna Vilanova
Published at EuroVis, 2003

We present a robust method for extracting 3D centerlines from volumetric datasets. We start from a 2D skeletonization method to locate voxels centered with respect to three orthogonal slicing directions. Next, we introduce a new detection criterion to extract the centerline voxels from the above skeletons, followed by a thinning, reconnection, and a ranking step. Overall, the proposed method produces centerlines that are object-centered, connected, one voxel thick, robust with respect to object noisiness, handles arbitrary object topologies, comes with a simple pruning threshold, and is fast to compute. We compare our results with two other methods on a variety of real-world datasets.
Accelerated Force Computation for Physics-Based Information Visualization
Authors: Ming C. Hao, Umeshwar Dayal, Daniel Cotting, Thomas Holenstein, Markus H. Gross
Published at EuroVis, 2003

Visualization of similarity is an emerging technique for analyzing relation-based data sets. A common way of computing the respective layouts in an information space is to employ a physics-based mass-spring system. Force computation, however, is costly and of order N2. In this paper, we propose a new acceleration method to adopt a well-known optimized force-computation algorithm which drastically reduces the computation time to the order of N log N. The basic idea is to derive a two-pass, "prediction and correction" procedure including a customized potential function. We have applied this method to two different applications: web access and sales analysis. Both demonstrate the efficiency and versatility of the presented method.
Adaptive Smooth Scattered Data Approximation for Large-scale Terrain Visualization
Authors: Martin Bertram 0001, Xavier Tricoche, Hans Hagen
Published at EuroVis, 2003

We present a fast method that adaptively approximates large-scale functional scattered data sets with hierarchical B-splines. The scheme is memory efficient, easy to implement and produces smooth surfaces. It combines adaptive clustering based on quadtrees with piecewise polynomial least squares approximations. The resulting surface components are locally approximated by a smooth B-spline surface obtained by knot removal. Residuals are computed with respect to this surface approximation, determining the clusters that need to be recursively refined, in order to satisfy a prescribed error bound. We provide numerical results for two terrain data sets, demonstrating that our algorithm works efficiently and accurate for large data sets with highly non-uniform sampling densities.
Analysis of HDAF for Interpolation and Noise Suppression in Volume Rendering
Authors: K. Anderson, Ioannis A. Kakadiaris, Manos Papadakis, Donald J. Kouri, David K. Hoffman
Published at EuroVis, 2003

In this paper, we evaluate the HDAF (Hermite Distributed Approximating Functionals) family of interpolation and derivative functions, with respect to their accuracy for reliable volume rendering, and compare them with other interpolation and derivative estimation filters. We utilize several different evaluation methods, both analytical and experimental. The former includes the order of decay of the global error, the local spatial error, and the behavior of the filters in the frequency domain. In the experimental part, visualizations of both synthetic and medical data are produced and studied. We show that the HDAFs exhibit superior behavior if the volumetric data are distorted by high frequency noise, and perform well under noise free conditions. This due to their ability to adjust the range of recovered frequencies.
Anti-Aliased Volume Extraction
Authors: Sarang Lakare, Arie E. Kaufman
Published at EuroVis, 2003

We present a technique to extract regions from a volumetric dataset without introducing any aliasing so that the extracted volume can be explored using direct volume rendering techniques. Extracting regions using binary masks generated by contemporary segmentation approaches typically introduces aliasing at the boundary of the extracted regions. This aliasing is especially visible when the dataset is visualized using direct volume rendering. Our algorithm uses the binary mask only to locate the boundary. The main idea of the algorithm is to retain the natural fuzziness at the boundary of a region even after it is extracted. To achieve that, intensities of the boundary voxels are flipped so that they are now representing a fuzzy boundary with the empty region surrounding it, while preserving the boundary position.
Case Study: Cellar Scaffold Extraction Using Crest Point for Volume Rendering
Authors: Jiuxiang Hu, D. Page Baluch, Anshuman Razdan, Gregory M. Nielson, Gerald E. Farin, David G. Capco
Published at EuroVis, 2003

Extraction of scaffolds, such as the meiotic spindles, a 3D tubular framework consisting of the microtubules, from conforcal laser scanning microscopy (CLSM) data of a cell is a challenge in biological image processing. It is of major importance in the research of microtubule anchor proteins, and molecular motor mechanics. However, the scaffold is hidden within CLSM data due to the nature of light excitation, and is difficult to visualize using traditional opacity and color transfer functions that depend only on local intensity. In this paper, we treat 3D CLSM data as a hyper-surface in R4, and show that the crest points of the hyper-surface correspond to the centerline of the hidden scaffold. We propose an automatic approach to extract the hidden scaffold from CLSM data. First, the spindle from the large data set is segmented using Weibull E-SD fields. We, next, apply the Savitzky-Golay (S-G) filter and Gaussian convolution to reduce the noise in the data and calculate the first and second derivatives. Lastly, direct volume rendering using ray casting is applied to visualize the volume data. We combine the local intensity and maximum curvature information to decide the opacity transfer function. Promising results are shown on simulated data sets as well as real CLSM data of mouse egg.
Case Study: Comparing Two Methods for Filtering External Motion in 4D Confocal Microscopy Data
Authors: Wim C. de Leeuw, Robert van Liere
Published at EuroVis, 2003

In this case study, we compare two methods for filtering external motion in time dependent volume data sets acquired from confocal microscopy. The pros and cons of a landmark based and a voxel based method are discussed. We show that filtering external motion is an essential first step for the visualization of confocal data.
Contouring Curved Quadratic Elements
Authors: David F. Wiley, Henry R. Childs, Benjamin F. Gregorski, Bernd Hamann, Kenneth I. Joy
Published at EuroVis, 2003

We show how to extract a contour line (or isosurface) from quadratic elements---specifically from quadratic triangles and tetrahedra. We also devise how to transform the resulting contour line (or surface) into a quartic curve (or surface) based on a curved-triangle (curved-tetrahedron) mapping. A contour in a bivariate quadratic function defined over a triangle in parameter space is a conic section and can be represented by a rational-quadratic function, while in physical space it is a rational quartic. An isosurface in the trivariate case is represented as a rational-quadratic patch in parameter space and a rational-quartic patch in physical space. The resulting contour surfaces can be rendered efficiently in hardware.
Detecting Critical Regions in Scalar Fields
Authors: Gunther H. Weber, Gerik Scheuermann, Bernd Hamann
Published at EuroVis, 2003

Trivariate data is commonly visualized using isosurfaces or direct volume rendering. When exploring scalar fields by isosurface extraction it is often difficult to choose isovalues that convey "useful" information. The significance of visualizations using direct volume rendering depends on the choice of good transfer functions. Understanding and using isosurface topology can help in identifying "relevant" isovalues for visualization via isosurfaces and can be used to automatically generate transfer functions.Critical isovalues indicate changes in topology of an isosurface: the creation of new surface components, merging of surface components or the formation of holes in a surface component. Interesting isosurface behavior is likely to occur at and around critical isovalues. Current approaches to detect critical isovalues are usually limited to isolated critical points. Data sets often contain regions of constant value (i.e., mesh edges, mesh faces, or entire mesh cells). We present a method that detects critical points, critical regions and corresponding critical isovalues for a scalar field defined by piecewise trilinear interpolation over a uniform rectilinear grid. We describe how to use the resulting list of critical regions/points and associated values to examine trivariate data.
Detection of constrictions on closed polyhedral surfaces
Authors: Franck Hétroy, Dominique Attali
Published at EuroVis, 2003

We define constrictions on a surface as simple closed geodesic curves, i.e. curves whose length is locally minimal. They can be of great interests in order to cut the surface in smaller parts. In this paper, we present a method to detect constrictions on closed triangulated surfaces. Our algorithm is based on a progressive approach. First, the surface is simplified by repeated edge collapses. The simplification continues until we detect an edge whose collapse would change the topology of the surface. It happens when three edges of the surface form a triangle that does not belong to the surface. The three edges define what we call a seed curve and are used to initialize the search of a constriction. Secondly, the constriction is progressively constructed by incrementally refining the simplified surface until the initial surface is retrieved. At each step of this refinement process, the constriction is updated. Some experimental results are provided.
Efficient Visualization of Large Medical Image Datasets on Standard PC Hardware
Authors: Vladimir Pekar, Daniel Hempel, Gundolf Kiefer, Marc Busch, Jürgen Weese
Published at EuroVis, 2003

Fast and accurate algorithms for medical image processing and visualization are becoming increasingly important due to routine acquisition and processing of rapidly growing amounts of data in clinical practice. At the same time, standard computer hardware is becoming sufficiently powerful to be used in applications which previously required expensive and inflexible special-purpose hardware. We present an efficient volume rendering approach using the example of maximum intensity projection (MIP), which is an important clinical tool. The method systematically exploits the properties of general-purpose hardware such as hierarchical cache memories and super-scalar processing. In order to optimize the cache efficiency, the dataset is processed in blocks which fit into the processor cache. The innermost ray casting loop is transformed such that the arithmetic operations and memory accesses can be processed in parallel on current general-purpose processors. Combined with other optimization strategies, such as vectorization and block-wise ray skipping, this approach yields near-interactive frame rates for large clinical datasets using a standard dual-processor PC. Data compression and simplification methods have intentionally not been used in order to demonstrate the achievable performance without any quality reductions. Some of the presented ideas can be applied to other computationally intensive image processing tasks.
Feature Flow Fields
Authors: Holger Theisel, Hans-Peter Seidel
Published at EuroVis, 2003

Feature tracking algorithms for instationary vector fields are usually based on a correspondence analysis of the features at different time steps. This paper introduces a method for feature tracking which is based on the integration of stream lines of a certain vector field called feature flow field. We analyze for which features the method of feature flow fields can be applied, we show how events in the flow can be detected using feature flow fields, and we show how to construct the feature flow fields for particular classes of features. Finally, we apply the technique to track critical points in a 2D instationary vector field.
Hardware-assisted View-dependent Isosurface Extraction using Spherical Partition
Authors: Jinzhu Gao, Han-Wei Shen
Published at EuroVis, 2003

Extracting only the visible portion of an isosurface can improve both the computation efficiency and the rendering speed. However, the visibility test overhead can be quite high for large scale data sets. In this paper, we present a view-dependent isosurface extraction algorithm utilizing occlusion query hardware to accelerate visible isosurface extraction. A spherical partition scheme is proposed to traverse the data blocks in a layered front-to-back order. Such traversal order helps our algorithm to identify the visible isosurface blocks more quickly with fewer visibility queries. Our algorithm can compute a more complete isosurface in a smaller amount of time, and thus is suitable for time-critical visualization applications.
Hierarchical Isosurface Segmentation Based on Discrete Curvature
Authors: Fabien Vivodtzev, Lars Linsen, Georges-Pierre Bonneau, Bernd Hamann, Kenneth I. Joy, Bruno A. Olshausen
Published at EuroVis, 2003

A high-level approach to describe the characteristics of a surface is to segment it into regions of uniform curvature behavior and construct an abstract representation given by a (topology) graph. We propose a surface segmentation method based on discrete mean and Gaussian curvature estimates. The surfaces are obtained from three-dimensional imaging data sets by isosurface extraction after data presmoothing and postprocessing the isosurfaces by a surface-growing algorithm. We generate a hierarchical multiresolution representation of the isosurface. Segmentation and graph generation algorithms can be performed at various levels of detail. At a coarse level of detail, the algorithm detects the main features of the surface. This low-resolution description is used to determine constraints for the segmentation and graph generation at the higher resolutions. We have applied our methods to MRI data sets of human brains. The hierarchical segmentation framework can be used for brain-mapping purposes.
Improving Topological Segmentation of Three-dimensional Vector Fields
Authors: Karim Mahrous, Janine Bennett, Bernd Hamann, Kenneth I. Joy
Published at EuroVis, 2003

We present three enhancements to accelerate the extraction of separatrices of three-dimensional vector fields, using intelligently selected "sample" streamlines. These enhancements reduce the number of needed sample streamlines and their propagation length. Inflow/outflow matching supports the simultaneous extraction of topologically significant inflow and outflow separatrices in a single pass. An adaptive sampling approach is introduced and used to seed streamlines in a more meaningful and efficient manner. Cell-locking is a new concept that isolates regions of a data set that do not contain separatrices. This concept makes streamline propagation more efficient as streamlines are not propagated through cells that do not influence or contain separatrices. These enhancements enable us to perform separatrix construction for three-dimensional vector field data requiring less overall computation.
Interaction of Light and Tensor Fields
Authors: Xiaoqiang Zheng, Alex Pang
Published at EuroVis, 2003

We present three new ways of looking at tensor volumes. All three methods are based on the interaction of simulated light and the tensor field. Conceptually, rays are shot from a certain direction into the tensor volume. These rays are influenced by the surrounding tensor field and bent as they traverse through the volume. The tensor is visualized by both the nature of the bent rays and by the collection of rays deposited on a receiving plate. The former is similar to streamlines, but shows paths of greatest influence by the tensor field. The latter is similar to caustic effects from photon maps, but shows the convergence or divergence of the rays through the tensor volume. We also use the concept of treating the tensor volume as a special lens that distorts an image. Using backward ray tracing through the tensor volume, we generate image distortions that also show internal properties of the tensor field. A key advantage of these techniques is that they can work directly with non-symmetric tensor fields without first decomposing them into components. Color images can also be found in www.soe.ucsc.edu/research/avis/tensorray.html.
Interactive Feature Specification for Focus+Context Visualization of Complex Simulation Data
Authors: Helmut Doleisch, Martin Gasser, Helwig Hauser
Published at EuroVis, 2003

Visualization of high-dimensional, large data sets, resulting from computational simulation, is one of the most challenging fields in scientific viualization. When visualization aims at supporting the analysis of such data sets, feature-based approches are very useful to reduce the amount of data which is shown at each instance of time and guide the user to the most interesting areas of the data. When using feature-based visualization, one of the most difficult questions is how to extract or specify the features. This is mostly done (semi-)automatic up to now. Especially when interactive analysis of the data is the main goal of the visualization, tools supporting interactive specification of features are needed.In this paper we present a framework for fiexible and interactive specification of high-dimensional and/or complex features in simulation data. The framework makes use of multiple, linked views from information as well as scienti c visualization and is based on a simple and compact feature definition language (FDL). It allows the definition of one or several features, which can be complex and/or hierarchically described by brushing multiple dimensions (using non-binary and composite brushes). The result of the specification is linked to all views, thereby a focus+context style of visualization in 3D is realized. To demonstrate the usage of the specification, as well as the linked tools, applications from flow simulation in the automotive industry are presented.
ISOSLIDER: A System for Interactive Exploration of Isosurfaces
Authors: Jatin Chhugani, Sudhir Vishwanath, Jonathan D. Cohen 0001, Subodh Kumar 0001
Published at EuroVis, 2003

We present ISOSLIDER, a system for interactive exploration of isosurfaces of a scalar field. Our algorithm focuses on fast update of isosurfaces for interactive display as a user makes small changes to the isovalue of the desired surface. We exploit the coherence of this update. Larger changes are supported as well. The update to the isosurface is made at a correct level of detail so that not too many operations need be performed nor too many triangles need be rendered. ISOSLIDER does not need to retain the entire volume in the main memory and stores most data out of core. The central idea of the ISOSLIDER algorithm is to determine salient isovalues where surface topology changes and pre-encode these changes so as to facilitate fast updates to the triangulation.