IEEE VIS Publication Dataset

We propose unsteady flow advection-convolution (UFAC) as a novel visualization approach for unsteady flows. It performs time evolution governed by pathlines, but builds spatial correlation according to instantaneous streamlines whose spatial extent is controlled by the flow unsteadiness. UFAC is derived from a generic framework that provides spacetime-coherent dense representations of time dependent-vector fields by a two-step process: 1) construction of continuous trajectories in spacetime for temporal coherence; and 2) convolution along another set of paths through the above spacetime for spatially correlated patterns. Within the framework, known visualization techniques-such as Lagrangian-Eulerian advection, image-based flow visualization, unsteady flow LIC, and dynamic LIC-can be reproduced, often with better image quality, higher performance, or increased flexibility of the visualization style. Finally, we present a texture-based discretization of the framework and its interactive implementation on graphics hardware, which allows the user to gradually balance visualization speed against quality.

The Internet pervades many aspects of our lives and is becoming indispensable to critical functions in areas such as commerce, government, production and general information dissemination. To maintain the stability and efficiency of the Internet, every effort must be made to protect it against various forms of attacks, malicious users, and errors. A key component in the Internet security effort is the routine examination of Internet routing data, which unfortunately can be too large and complicated to browse directly. We have developed an interactive visualization process which proves to be very effective for the analysis of Internet routing data. In this application paper, we show how each step in the visualization process helps direct the analysis and glean insights from the data. These insights include the discovery of patterns, detection of faults and abnormal events, understanding of event correlations, formation of causation hypotheses, and classification of anomalies. We also discuss lessons learned in our visual analysis study.

We present techniques for discovering and exploiting regularity in large curvilinear data sets. The data can be based on a single mesh or a mesh composed of multiple submeshes (also known as zones). Multi-zone data are typical in Computational Fluid Dynamics (CFD) simulations. Regularities include axis-aligned rectilinear and cylindrical meshes as well as cases where one zone is equivalent to a rigid body transformation of another. Our algorithms can also discover rigid-body motion of meshes in time-series data. Next, we describe a data model where we can utilize the results from the discovery process in order to accelerate large data visualizations. Where possible, we replace general curvilinear zones with rectilinear or cylindrical zones. In rigid-body motion cases, we replace a time-series of meshes with a transformed mesh object where a reference mesh is dynamically transformed based on a given time value in order to satisfy geometry requests, on demand. The data model enables us to make these substitutions and dynamic transformations transparently with respect to the visualization algorithms. We present results with large data sets where we combine our mesh replacement and transformation techniques with out-of-core paging in order to achieve analysis speedups ranging from 1.5 to 2.

Nowadays, direct volume rendering via 3D textures has positioned itself as an efficient tool for the display and visual analysis of volumetric scalar fields. It is commonly accepted, that for reasonably sized data sets appropriate quality at interactive rates can be achieved by means of this technique. However, despite these benefits one important issue has received little attention throughout the ongoing discussion of texture based volume rendering: the integration of acceleration techniques to reduce per-fragment operations. In this paper, we address the integration of early ray termination and empty-space skipping into texture based volume rendering on graphical processing units (GPU). Therefore, we describe volume ray-casting on programmable graphics hardware as an alternative to object-order approaches. We exploit the early z-test to terminate fragment processing once sufficient opacity has been accumulated, and to skip empty space along the rays of sight. We demonstrate performance gains up to a factor of 3 for typical renditions of volumetric data sets on the ATI 9700 graphics card.

While there are a couple of transfer function design approaches for CT and MRI (magnetic resonance imaging) data, direct volume rendering of ultrasound data still relies on manual adjustment of an inflexible piecewise linear opacity transfer function (OTF) on a trial-and-error basis. The main challenge of automatically designing an OTF for visualization of sonographic data is the low signal-to-noise ratio in combination with real time data acquisition at frame rates up to 25 volumes per second. In this paper, we present an efficient solution of this task. Our approach is based on the evaluation of tube cores, i.e., collections of voxels gathered by traversing the volume in rendering directions. We use information about the probable position of an interface between tissues of different echogenicity to adaptively design an OTF in a multiplicative way. We show the appropriateness of our approach by examples, deliberately on data sets of moderate quality arising frequently in clinical settings.

Traditional volume visualization techniques may provide incomplete clinical information needed for applications in medical visualization. In the area of vascular visualization important features such as the lumen of a diseased vessel segment may not be visible. Curved planar reformation (CPR) has proven to be an acceptable practical solution. Existing CPR techniques, however, still have diagnostically relevant limitations. In this paper, we introduce two advances methods for efficient vessel visualization, based on the concept of CPR. Both methods benefit from relaxation of spatial coherence in favor of improved feature perception. We present a new technique to visualize the interior of a vessel in a single image. A vessel is resampled along a spiral around its central axis. The helical spiral depicts the vessel volume. Furthermore, a method to display an entire vascular tree without mutually occluding vessels is presented. Minimal rotations at the bifurcations avoid occlusions. For each viewing direction the entire vessel structure is visible.

In this paper a new quadric-based view-dependent simplification scheme is presented. The scheme provides a method to connect mesh simplification controlled by a quadric error metric with a level-of-detail hierarchy that is accessed continuously and efficiently based on current view parameters. A variety of methods for determining the screen-space metric for the view calculation are implemented and evaluated, including an appearance-preserving method that has both geometry- and texture-preserving aspects. Results are presented and compared for a variety of models.

In this paper we present an interactive texture-based technique for visualizing three-dimensional vector fields. The goal of the algorithm is to provide a general volume rendering framework allowing the user to compute three-dimensional flow textures interactively, and to modify the appearance of the visualization on the fly. To achieve our goal, we decouple the visualization pipeline into two disjoint stages. First, streamlines are generated from the 3D vector data. Various geometric properties of the streamlines are extracted and converted into a volumetric form using a hardware-assisted slice sweeping algorithm. In the second phase of the algorithm, the attributes stored in the volume are used as texture coordinates to look up an appearance texture to generate both informative and aesthetic representations of the underlying vector field. Users can change the input textures and instantaneously visualize the rendering results. With our algorithm, visualizations with enhanced structural perception using various visual cues can be rendered in real time. A myriad of existing geometry-based and texture-based visualization techniques can also be emulated.

The goal of this paper is to define a convolution operation which transfers image processing and pattern matching to vector fields from flow visualization. For this, a multiplication of vectors is necessary. Clifford algebra provides such a multiplication of vectors. We define a Clifford convolution on vector fields with uniform grids. The Clifford convolution works with multivector filter masks. Scalar and vector masks can be easily converted to multivector fields. So, filter masks from image processing on scalar fields can be applied as well as vector and scalar masks. Furthermore, a method for pattern matching with Clifford convolution on vector fields is described. The method is independent of the direction of the structures. This provides an automatic approach to feature detection. The features can be visualized using any known method like glyphs, isosurfaces or streamlines. The features are defined by filter masks instead of analytical properties and thus the approach is more intuitive.

A survey of graphics developers on the issue of texture mapping hardware for volume rendering would most likely find that the vast majority of them view limited texture memory as one of the most serious drawbacks of an otherwise fine technology. In this paper, we propose a compression scheme for static and time-varying volumetric data sets based on vector quantization that allows us to circumvent this limitation. We describe a hierarchical quantization scheme that is based on a multiresolution covariance analysis of the original field. This allows for the efficient encoding of large-scale data sets, yet providing a mechanism to exploit temporal coherence in non-stationary fields. We show, that decoding and rendering the compressed data stream can be done on the graphics chip using programmable hardware. In this way, data transfer between the CPU and the graphics processing unit (GPU) can be minimized thus enabling flexible and memory efficient real-time rendering options. We demonstrate the effectiveness of our approach by demonstrating interactive renditions of Gigabyte data sets at reasonable fidelity on commodity graphics hardware.

Hand-crafted illustrations are often more effective than photographs for conveying the shape and important features of an object, but they require expertise and time to produce. We describe an image compositing system and user interface that allow an artist to quickly and easily create technical illustrations from a set of photographs of an object taken from the same point of view under variable lighting conditions. Our system uses a novel compositing process in which images are combined using spatially-varying light mattes, enabling the final lighting in each area of the composite to be manipulated independently. We describe an interface that provides for the painting of local lighting effects (e.g. shadows, highlights, and tangential lighting to reveal texture) directly onto the composite. We survey some of the techniques used in illustration and lighting design to convey the shape and features of objects and describe how our system can be used to apply these techniques.

We describe how to count the cases that arise in a family of visualization techniques, including marching cubes, sweeping simplices, contour meshing, interval volumes, and separating surfaces. Counting the cases is the first step toward developing a generic visualization algorithm to produce substitopes (geometric substitution of polytopes). We demonstrate the method using a software system ("GAP") for computational group theory. The case-counts are organized into a table that provides taxonomy of members of the family; numbers in the table are derived from actual lists of cases, which are computed by our methods. The calculation confirms previously reported case-counts for large dimensions that are too large to check by hand, and predicts the number of cases that will arise in algorithms that have not yet been invented.

Direct volume rendering of scalar fields uses a transfer function to map locally measured data properties to opacities and colors. The domain of the transfer function is typically the one-dimensional space of scalar data values. This paper advances the use of curvature information in multi-dimensional transfer functions, with a methodology for computing high-quality curvature measurements. The proposed methodology combines an implicit formulation of curvature with convolution-based reconstruction of the field. We give concrete guidelines for implementing the methodology, and illustrate the importance of choosing accurate filters for computing derivatives with convolution. Curvature-based transfer functions are shown to extend the expressivity and utility of volume rendering through contributions in three different application areas: nonphotorealistic volume rendering, surface smoothing via anisotropic diffusion, and visualization of isosurface uncertainty.

In this paper we offer several new insights and techniques for effectively using color and texture to simultaneously convey information about multiple 2D scalar and vector distributions, in a way that facilitates allowing each distribution to be understood both individually and in the context of one or more of the other distributions. Specifically, we introduce the concepts of: color weaving for simultaneously representing information about multiple co-located color encoded distributions; and texture stitching for achieving more spatially accurate multi-frequency line integral convolution representations of combined scalar and vector distributions. The target application for our research is the definition, detection and visualization of regions of interest in a turbulent boundary layer flow at moderate Reynolds number. In this work, we examine and analyze streamwise-spanwise planes of three-component velocity vectors with the goal of identifying and characterizing spatially organized packets of hairpin vortices.

We propose methods to accelerate texture-based volume rendering by skipping invisible voxels. We partition the volume into sub-volumes, each containing voxels with similar properties. Sub-volumes composed of only voxels mapped to empty by the transfer function are skipped. To render the adaptively partitioned sub-volumes in visibility order, we reorganize them into an orthogonal BSP tree. We also present an algorithm that computes incrementally the intersection of the volume with the slicing planes, which avoids the overhead of the intersection and texture coordinates computation introduced by the partitioning. Rendering with empty space skipping is 2 to 5 times faster than without it. To skip occluded voxels, we introduce the concept of orthogonal opacity map, that simplifies the transformation between the volume coordinates and the opacity map coordinates, which is intensively used for occlusion detection. The map is updated efficiently by the GPU. The sub-volumes are then culled and clipped against the opacity map. We also present a method that adaptively adjusts the optimal number of the opacity map updates. With occlusion clipping, about 60% of non-empty voxels can be skipped and an additional 80% speedup on average is gained for iso-surface-like rendering.

The extraction of planar sections from volume images is the most commonly used technique for inspecting and visualizing anatomic structures. We propose to generalize the concept of planar section to the extraction of curved cross-sections (free form surfaces). Compared with planar slices, curved cross-sections may easily follow the trajectory of tubular structures and organs such as the aorta or the colon. They may be extracted from a 3D volume, displayed as a 3D view and possibly flattened. Flattening of curved cross-sections allows to inspect spatially complex relationship between anatomic structures and their neighborhood. They also allow to carry out measurements along a specific orientation. For the purpose of facilitating the interactive specification of free form surfaces, users may navigate in real time within the body and select the slices on which the surface control points will be positioned. Immediate feedback is provided by displaying boundary curves as cylindrical markers within a 3D view composed of anatomic organs, planar slices and possibly free form surface sections. Extraction of curved surface sections is an additional service that is available online as a Java applet (http://visiblehuman.epfl.ch). It may be used as an advanced tool for exploring and teaching anatomy.

There are numerous algorithms in graphics and visualization whose performance is known to decay as the topological complexity of the input increases. On the other hand, the standard pipeline for 3D geometry acquisition often produces 3D models that are topologically more complex than their real forms. We present a simple and efficient algorithm that allows us to simplify the topology of an isosurface by alternating the values of some number of voxels. Its utility and performance are demonstrated on several examples, including signed distance functions from polygonal models and CT scans.

Volume rendering and isosurface extraction from three-dimensional scalar fields are mostly based on piecewise trilinear representations. In regions of high geometric complexity such visualization methods often exhibit artifacts, due to trilinear interpolation. In this work, we present an iterative fairing method for scalar fields interpolating function values associated with grid points while smoothing the contours inside the grid cells based on variational principles. We present a local fairing method providing a piecewise bicubic representation of two-dimensional scalar fields. Our algorithm generalizes to the trivariate case and can be used to increase the resolution of data sets either locally or globally, reducing interpolation artifacts. In contrast to filtering methods, our algorithm does not reduce geometric detail supported by the data.

Segmentation of structures from measured volume data, such as anatomy in medical imaging, is a challenging data-dependent task. In this paper, we present a segmentation method that leverages the parallel processing capabilities of modern programmable graphics hardware in order to run significantly faster than previous methods. In addition, collocating the algorithm computation with the visualization on the graphics hardware circumvents the need to transfer data across the system bus, allowing for faster visualization and interaction. This algorithm is unique in that it utilizes sophisticated graphics hardware functionality (i.e., floating point precision, render to texture, computational masking, and fragment programs) to enable fast segmentation and interactive visualization.