IEEE VIS Publication Dataset

This paper introduces a method for smoothing complex, noisy surfaces, while preserving (and enhancing) sharp, geometric features. It has two main advantages over previous approaches to feature preserving surface smoothing. First is the use of level set surface models, which allows us to process very complex shapes of arbitrary and changing topology. This generality makes it well suited for processing surfaces that are derived directly from measured data. The second advantage is that the proposed method derives from a well-founded formulation, which is a natural generalization of anisotropic diffusion, as used in image processing. This formulation is based on the proposition that the generalization of image filtering entails filtering the normals of the surface, rather than processing the positions of points on a mesh.

In this paper, we present a verification algorithm for swirling features in flow fields, based on the geometry of streamlines. The features of interest in this case are vortices. Without a formal definition, existing detection algorithms lack the ability to accurately identify these features, and the current method for verifying the accuracy of their results is by human visual inspection. Our verification algorithm addresses this issue by automating the visual inspection process. It is based on identifying the swirling streamlines that surround the candidate vortex cores. We apply our algorithm to both numerically simulated and procedurally generated datasets to illustrate the efficacy of our approach.

We present a technique to perform occlusion culling for hierarchical terrains at run-time. The algorithm is simple to implement and requires minimal pre-processing and additional storage, yet leads to 2-4 times improvement in framerate for views with high degrees of occlusion. Our method is based on the well-known occlusion horizon algorithm. We show how to adapt the algorithm for use with hierarchical terrains. The occlusion horizon is constructed as the terrain is traversed in an approximate front to back ordering. Regions of the terrain are compared to the horizon to determine when they are completely occluded from the viewpoint. Culling these regions leads to significant savings in rendering.

This paper is a documentation of techniques invented, results obtained and lessons learned while creating visualization algorithms to render outputs of large-scale seismic simulations. The objective is the development of techniques for a collaborative simulation and visualization shared between structural engineers, seismologists, and computer scientists. The computer graphics research community has been witnessing a large number of exemplary publications addressing the challenges faced while trying to visualize both large-scale surface and volumetric datasets lately. From a visualization perspective, issues like data preprocessing (simplification, sampling, filtering, etc.); rendering algorithms (surface and volume), and interaction paradigms (large-scale, highly interactive, highly immersive, etc.) have been areas of study. In this light, we outline and describe the milestones achieved in a large-scale simulation and visualization project, which opened the scope for combining existing techniques with new methods, especially in those cases where no existing methods were suitable. We elucidate the data simplification and reorganization schemes that we used, and discuss the problems we encountered and the solutions we found. We describe both desktop (high-end local as well as remote) interfaces and immersive visualization systems that we developed to employ interactive surface and volume rendering algorithms. Finally, we describe the results obtained, challenges that still need to be addressed, and ongoing efforts to meet the challenges of large-scale visualization.

We discuss 3d interaction techniques for the quantitative analysis of spatial relations in medical visualizations. We describe the design and implementation of measurement tools to measure distances, angles and volumes in 3d visualizations. The visualization of measurement tools as recognizable 3d objects and a 3d interaction, which is both intuitive and precise, determines the usability of such facilities. Measurements may be carried out in 2d visualizations of the original radiological data and in 3d visualizations. The result of a measurement carried out in one view is also displayed in the other view appropriately. We discuss the validation of the obtained measures. Finally, we describe how some important measurement tasks may be solved automatically.

We present a new algorithm for rendering very large volume data sets at interactive frame rates on standard PC hardware. The algorithm accepts scalar data sampled on a regular grid as input. The input data is converted into a compressed hierarchical wavelet representation in a preprocessing step. During rendering, the wavelet representation is decompressed on-the-fly and rendered using hardware texture mapping. The level of detail used for rendering is adapted to the local frequency spectrum of the data and its position relative to the viewer. Using a prototype implementation of the algorithm we were able to perform an interactive walkthrough of large data sets such as the visible human on a single off-the-shelf PC.

We describe a method for volume rendering using a spectral representation of colour instead of the traditional RGB model. It is shown how to use this framework for a novel exploration of datasets through enhanced transfer function design. Furthermore, our framework is extended to allow real-time re-lighting of the scene created with any rendering method. The technique of post-illumination is introduced to generate new spectral images for arbitrary light colours in real-time. Also a tool is described to design a palette of lights and materials having certain properties such as selective metamerism or colour constancy. Applied to spectral transfer functions, different light colours can accentuate or hide specific qualities of the data. In connection with post-illumination this provides a new degree of freedom for guided exploration of volumetric data, which cannot be achieved using the RGB model.

Direct volume rendering is a commonly used technique in visualization applications. Many of these applications require sophisticated shading models to capture subtle lighting effects and characteristics of volumetric data and materials. Many common objects and natural phenomena exhibit visual quality that cannot be captured using simple lighting models or cannot be solved at interactive rates using more sophisticated methods. We present a simple yet effective interactive shading model which captures volumetric light attenuation effects to produce volumetric shadows and the subtle appearance of translucency. We also present a technique for volume displacement or perturbation that allows realistic interactive modeling of high frequency detail for real and synthetic volumetric data.

We present an algorithm for interactively extracting and rendering isosurfaces of large volume datasets in a view-dependent fashion. A recursive tetrahedral mesh refinement scheme, based on longest edge bisection, is used to hierarchically decompose the data into a multiresolution structure. This data structure allows fast extraction of arbitrary isosurfaces to within user specified view-dependent error bounds. A data layout scheme based on hierarchical space filling curves provides access to the data in a cache coherent manner that follows the data access pattern indicated by the mesh refinement.

We present a method for interactive rendering of large outdoor scenes. Complex polygonal plant models and whole plant populations are represented by relatively small sets of point and line primitives. This enables us to show landscapes faithfully using only a limited percentage of primitives. In addition, a hierarchical data structure allows us to smoothly reduce the geometrical representation to any desired number of primitives. The scene is hierarchically divided into local portions of geometry to achieve large reduction factors for distant regions. Additionally, the data reduction is adapted to the visual importance of geometric objects. This allows us to maintain the visual fidelity of the representation while reducing most of the geometry drastically. With our system, we are able to interactively render very complex landscapes with good visual quality.

To display the intuitive meaning of an abstract metric it is helpful to look on an embedded surface with the same inner geometry as the given metric. The resulting partial differential equations have no standard solution. Only for some special cases satisfactory methods are known. I present a new algorithmic approach which is not based on differential equations. In contrast to other methods this technique also works if the embedding exists only locally. The fundamental idea is to estimate Euclidean distances, from which the surface is built up. In this paper I focus on the reconstruction of a surface from these estimated distances. Particular the influence of a perturbation of the distances on the shape of the resulting surface is investigated.

Motion provides strong visual cues for the perception of shape and depth, as demonstrated by cognitive scientists and visual artists. This paper presents a novel visualization technique-kinetic visualization -that uses particle systems to add supplemental motion cues which can aid in the perception of shape and spatial relationships of static objects. Based on a set of rules following perceptual and physical principles, particles flowing over the surface of an object not only bring out, but also attract attention to, essential information on the shape of the object that might not be readily visible with conventional rendering that uses lighting and view changes. Replacing still images with animations in this fashion, we demonstrate with both surface and volumetric models in the accompanying videos that in many cases the resulting visualizations effectively enhance the perception of three-dimensional shape and structure. The results of a preliminary user study that we have conducted also show evidence that the supplemental motion cues help.

Typically 3-D MR and CT scans have a relatively high resolution in the scanning X-Y plane, but much lower resolution in the axial Z direction. This non-uniform sampling of an object can miss small or thin structures. One way to address this problem is to scan the same object from multiple directions. In this paper we describe a method for deforming a level set model using velocity information derived from multiple volume datasets with non-uniform resolution in order to produce a single high-resolution 3D model. The method locally approximates the values of the multiple datasets by fitting a distance-weighted polynomial using moving least-squares. The proposed method has several advantageous properties: its computational cost is proportional to the object surface area, it is stable with respect to noise, imperfect registrations and abrupt changes in the data, it provides gain-correction, and it employs a distance-based weighting to ensures that the contributions from each scan are properly merged into the final result. We have demonstrated the effectiveness of our approach on four multi-scan datasets, a Griffin laser scan reconstruction, a CT scan of a teapot and MR scans of a mouse embryo and a zucchini.

Finding the "best" viewing parameters for a scene is a difficult but very important problem. Fully automatic procedures seem to be impossible as the notion of "best" strongly depends on human judgment as well as on the application. In this paper a solution to the sub-problem of placing light sources for given camera parameters is proposed. A light position is defined to be optimal, when the resulting illumination reveals more about the scene than illuminations from all other light positions, i.e. the light position maximizes information that is added to the image through the illumination. With the help of an experiment with several subjects we could adapt the information measure to the actually perceived information content. We present fast global optimization procedures and solutions for two and more light sources.

This paper examines a series of NASA outreach visualizations created using several layers of remote sensing satellite data ranging from 4-kilometers per pixel to I-meter per pixel. The viewer is taken on a seamless, cloud free journey from a global view of the Earth down to ground level where buildings, streets, and cars are visible. The visualizations were produced using a procedural shader that takes advantage of accurate georegistration and color matching between images. The shader accurately and efficiently maps the data sets to geometry allowing for animations with few perceptual transitions among data sets. We developed a pipeline to facilitate the production of over twenty zoom visualizations. Millions of people have seen these visualizations through national and international media coverage.

Simulating hand-drawn illustration techniques can succinctly express information in a manner that is communicative and informative. We present a framework for an interactive direct volume illustration system that simulates traditional stipple drawing. By combining the principles of artistic and scientific illustration, we explore several feature enhancement techniques to create effective, interactive visualizations of scientific and medical datasets. We also introduce a rendering mechanism that generates appropriate point lists at all resolutions during an automatic preprocess, and modifies rendering styles through different combinations of these feature enhancements. The new system is an effective way to interactively preview large, complex volume datasets in a concise, meaningful, and illustrative manner. Volume stippling is effective for many applications and provides a quick and efficient method to investigate volume models.

In this paper we are presenting a novel approach for rendering large datasets in a view-dependent manner. In a typical view-dependent rendering framework, an appropriate level of detail is selected and sent to the graphics hardware for rendering at each frame. In our approach, we have successfully managed to speed up the selection of the level of detail as well as the rendering of the selected levels. We have accelerated the selection of the appropriate level of detail by not scanning active nodes that do not contribute to the incremental update of the selected level of detail. Our idea is based on imposing a spatial subdivision over the view-dependence trees data-structure, which allows spatial tree cells to refine and merge in real-time rendering to comply with the changes in the active nodes list. The rendering of the selected level of detail is accelerated by using vertex arrays. To overcome the dynamic changes in the selected levels of detail we use multiple small vertex arrays whose sizes depend on the memory on the graphics hardware. These multiple vertex arrays are attached to the active cells of the spatial tree and represent the active nodes of these cells. These vertex arrays, which are sent to the graphics hardware at each frame, merge and split with respect to the changes in the cells of the spatial tree.

In this paper we develop a new technique for tracing anatomical fibers from 3D tensor fields. The technique extracts salient tensor features using a local regularization technique that allows the algorithm to cross noisy regions and bridge gaps in the data. We applied the method to human brain DT-MRI data and recovered identifiable anatomical structures that correspond to the white matter brain-fiber pathways. The images in this paper are derived from a dataset having 121×88×60 resolution. We were able to recover fibers with less than the voxel size resolution by applying the regularization technique, i.e., using a priori assumptions about fiber smoothness. The regularization procedure is done through a moving least squares filter directly incorporated in the tracing algorithm.

We present an external memory algorithm for fast display of very large and complex geometric environments. We represent the model using a scene graph and employ different culling techniques for rendering acceleration. Our algorithm uses a parallel approach to render the scene as well as fetch objects from the disk in a synchronous manner. We present a novel prioritized prefetching technique that takes into account LOD-switching and visibility-based events between successive frames. We have applied our algorithm to large gigabyte-sized environments that are composed of thousands of objects and tens of millions of polygons. The memory overhead of our algorithm is output sensitive and is typically tens of megabytes. In practice, our approach scales with the model sizes, and its rendering performance is comparable to that of an in-core algorithm.

Within the field of computer graphics and visualization, it is often necessary to visualize polygonal models with large number of polygons. Display quality is mandatory, but it is also desirable to have the ability to rapidly update the display in order to facilitate interactive use. Point based rendering methods have been shown effective for this task. Building on this paradigm we introduce the PMR system which uses a hierarchy both in points and triangles for rendering. This hierarchy is fundamentally different from the ones used in existing methods. It is based on the feature geometry in the object space rather than its projection in the screen space. This provides certain advantages over the existing methods.