IEEE VIS Publication Dataset

We present an efficient algorithm to mesh the macromolecules surface model represented by the skin surface defined by Edelsbrunner. Our algorithm overcomes several challenges residing in current surface meshing methods. First, we guarantee the mesh quality with a provable lower bound of 21┬░ on its minimum angle. Second, we ensure the triangulation is homeomorphic to the original surface. Third, we improve the efficiency of constructing the restricted Delaunay triangulation (RDT) of smooth surfaces. We achieve this by constructing the RDT using the advancing front method without computing the Delaunay tetrahedrization of the sample points on the surfaces. The difficulty of handling the front collision problem is tackled by employing the Morse theory. In particular, we construct the Morse-Smale complex to simplify the topological changes of the front. Our implementation results suggest that the algorithm decrease the time of generating high quality homeomorphic skin mesh from hours to a few minutes.

Surface texture is among the most salient haptic characteristics of objects; it can induce vibratory contact forces that lead to perception of roughness. We present a new algorithm to display haptic texture information resulting from the interaction between two textured objects. We compute contact forces and torques using low-resolution geometric representations along with texture images that encode surface details. We also introduce a novel force model based on directional penetration depth and describe an efficient implementation on programmable graphics hardware that enables interactive haptic texture rendering of complex models. Our force model takes into account important factors identified by psychophysics studies and is able to haptically display interaction due to fine surface textures that previous algorithms do not capture.

We present a hardware-accelerated adaptive EWA (elliptical weighted average) volume splatting algorithm. EWA splatting combines a Gaussian reconstruction kernel with a low-pass image filter for high image quality without aliasing artifacts or excessive blurring. We introduce a novel adaptive filtering scheme to reduce the computational cost of EWA splatting. We show how this algorithm can be efficiently implemented on modern graphics processing units (GPUs). Our implementation includes interactive classification and fast lighting. To accelerate the rendering we store splat geometry and 3D volume data locally in GPU memory. We present results for several rectilinear volume datasets that demonstrate the high image quality and interactive rendering speed of our method.

Modern object-oriented programs are hierarchical systems with many thousands of interrelated subsystems. Visualization helps developers to better comprehend these large and complex systems. This work presents a three-dimensional visualization technique that represents the static structure of object-oriented software using distributions of three-dimensional objects on a two-dimensional plane. The visual complexity is reduced by adjusting the transparency of object surfaces to the distance of the viewpoint. An approach called Hierarchical Net is proposed for a clear representation of the relationships between the subsystems.

ImageSurfer is a tool designed to explore correlations between two 3D scalar fields. Our scientific goal was to determine where a protein is located, and how much its concentration varies along the membrane of a neuronal dendrite. The 3D scalar field data sets fall into two categories: dendritic plasma membranes (defining the structure) and immunofluorescent staining (defining protein concentration along the structure). ImageSurfer enables scientists to analyze relationships between multiple data sets obtained with confocal microscopy by providing 3D surface view, height field, and graphing tools. Each tool reduces the complexity of the problem by extracting a restricted subset of data: finding a region of interest in 3D; getting a sense of relative concentrations in 2D, and getting exact concentration values in 1D. The current design is presented, along with the rationale for each design decision. The tool is already proving useful for data exploration, analysis, and presentation.

This work presents an experimental immersive interface for designing DNA components for application in nanotechnology. While much research has been done on immersive visualization, this is one of the first systems to apply advanced interface techniques to a scientific design problem. This system uses tangible 3D input devices (tongs, a raygun, and a multipurpose handle tool) to create and edit a purely digital representation of DNA. The tangible controllers are associated with functions (not data) while a virtual display is used to render the model. This interface was built in collaboration with a research group investigating the design of DNA tiles. A user study shows that scientists find the immersive interface more satisfying than a 2D interface due to the enhanced understanding gained by directly interacting with molecules in 3D space.

This work introduces importance-driven volume rendering as a novel technique for automatic focus and context display of volumetric data. Our technique is a generalization of cut-away views, which - depending on the viewpoint - remove or suppress less important parts of a scene to reveal more important underlying information. We automatize and apply this idea to volumetric data. Each part of the volumetric data is assigned an object importance, which encodes visibility priority. This property determines which structures should be readily discernible and which structures are less important. In those image regions, where an object occludes more important structures it is displayed more sparsely than in those areas where no occlusion occurs. Thus the objects of interest are clearly visible. For each object several representations, i.e., levels of sparseness, are specified. The display of an individual object may incorporate different levels of sparseness. The goal is to emphasize important structures and to maximize the information content in the final image. This work also discusses several possible schemes for level of sparseness specification and different ways how object importance can be composited to determine the final appearance of a particular object.

Multiperspective images are a useful way to visualize extended, roughly planar scenes such as landscapes or city blocks. However, constructing effective multiperspective images is something of an art. We describe an interactive system for creating multiperspective images composed of serially blended cross-slits images. Beginning with a sideways-looking video of the scene as might be captured from a moving vehicle, we allow the user to interactively specify a set of cross-slits cameras, possibly with gaps between them. In each camera, one of the slits is defined to be the camera path, which is typically horizontal, and the user is left to choose the second slit, which is typically vertical. The system then generates intermediate views between these cameras using a novel interpolation scheme, thereby producing a multiperspective image with no seams. The user can also choose the picture surface in space onto which viewing rays are projected, thereby establishing a parameterization for the image. We show how the choice of this surface can be used to create interesting visual effects. We demonstrate our system by constructing multiperspective images that summarize city blocks, including corners, blocks with deep plazas and other challenging urban situations.

Datasets of tens of gigabytes are becoming common in computational and experimental science. This development is driven by advances in imaging technology, producing detectors with growing resolutions, as well as availability of cheap processing power and memory capacity in commodity-based computing clusters. We describe the design of a visualization system that allows scientists to interactively explore large remote data sets in an efficient and flexible way. The system is broadly applicable and currently used by medical scientists conducting an osteoporosis research project. Human vertebral bodies are scanned using a high resolution microCT scanner producing scans of roughly 8 GB size each. All participating research groups require access to the centrally stored data. Due to the rich internal bone structure, scientists need to interactively explore the full dataset at coarse levels, as well as visualize subvolumes of interest at the highest resolution. Our solution is based on HDF5 and GridFTP. When accessing data remotely, the HDF5 data processing pipeline is modified to support efficient retrieval of subvolumes. We reduce the overall latency and optimize throughput by executing high-level operations on the remote side. The GridFTP protocol is used to pass the HDF5 requests to a customized server. The approach takes full advantage of local graphics hardware for rendering. Interactive visualization is accomplished using a background thread to access the datasets stored in a multiresolution format. A hierarchical volume tenderer provides seamless integration of high resolution details with low resolution overviews.

We propose a novel point-based approach to view dependent isosurface extraction. We introduce a fast visibility query system for the view dependent traversal, which exhibits moderate memory requirements. This technique allows for an interactive interrogation of the full visible woman dataset (1GB) at four to fifteen frames per second on a desktop computer. The point-based approach is built on an extraction scheme that classifies different sections of the isosurface into four categories, depending on the size of the geometry when projected onto the screen. In particular, we use points to represent small and subpixel triangles, as well as larger sections of the isosurface whose projection has subpixel size. To assign consistent and robust normals to individual points representing such regions, we propose to compute them during post processing of the extracted isosurface and provide the corresponding hardware implementation.

The visualization of any vector field is dependent on the relative velocity of the observer. In experimentally generated vector fields, the average value of the streamwise component of the global vector field is typically calculated and subtracted from each vector. We demonstrate that the resulting image, critical points, and vector field features are greatly influenced by the magnitude of the value subtracted from the streamwise velocity.

This work describes the methods used to produce an interactive visualization of a 2 TB computational fluid dynamics (CFD) data set using particle tracing (streaklines). We use the method introduced by Bruckschen el al. (2001) that precomputes a large number of particles, stores them on disk using a space-filling curve ordering that minimizes seeks, then retrieves and displays the particles according to the user's command. We describe how the particle computation can be performed using a PC cluster, how the algorithm can be adapted to work with a multiblock curvilinear mesh, how scalars can be extracted and used to color the particles, and how the out-of-core visualization can be scaled to 293 billion particles while still achieving interactive performance on PC hardware. Compared to the earlier work, our data set size and total number of particles are an order of magnitude larger. We also describe a new compression technique that losslessly reduces the amount of particle storage by 41% and speeds the particle retrieval by about 20%.

This work describes a method to visualize the thickness of curved thin objects. Given the MRI volume data of articular cartilage, medical doctors investigate pathological changes of the thickness. Since the tissue is very thin, it is impossible to reliably map the thickness information by direct volume rendering. Our idea is based on unfolding of such structures preserving their thickness. This allows to perform anisotropic geometrical operations (e.g., scaling the thickness). However, flattening of a curved structure implies a distortion of its surface. The distortion problem is alleviated through a focus-and-context minimization approach. Distortion is smallest close to a focal point which can be interactively selected by the user.

Virtual prototyping is increasingly replacing real mock-ups and experiments in industrial product development. Part of this process is the simulation of structural and functional properties, which is in many cases based on finite element analysis (FEA). One prominent example from the automotive industry is the safety improvement resulting from crash worthiness simulations. A simulation model for this purpose usually consists of up to one million finite elements and is assembled from many parts, which are individually meshed out of their CAD representation. In order to accelerate the development cycle, simulation engineers want to be able to modify their FE models without going back to the CAD department. Furthermore, valid CAD models might even not be available in preliminary design stages. However, in contrast to CAD, there is a lack of tools that offer the possibility of modification and processing of finite element components while maintaining the properties relevant to the simulation. In this application paper we present interactive algorithms for intuitive and fast editing of FE models and appropriate visualization techniques to support engineers in understating these models. This includes new kinds of manipulators, feedback mechanisms and facilities for virtual reality and immersion at the workplace, e.g. autostereoscopic displays and haptic devices.

We investigate two important, common fluid flow patterns from computational fluid dynamics (CFD) simulations, namely, swirl and tumble motion typical of automotive engines. We study and visualize swirl and tumble flow using three different flow visualization techniques: direct, geometric, and texture-based. When illustrating these methods side-by-side, we describe the relative strengths and weaknesses of each approach within a specific spatial dimension and across multiple spatial dimensions typical of an engineer's analysis. Our study is focused on steady-state flow. Based on this investigation we offer perspectives on where and when these techniques are best applied in order to visualize the behavior of swirl and tumble motion.

We introduce Light Collages - a lighting design system for effective visualization based on principles of human perception. Artists and illustrators enhance perception of features with lighting that is locally consistent and globally inconsistent. Inspired by these techniques, we design the placement of light sources to convey a greater sense of realism and better perception of shape with globally inconsistent lighting. Our algorithm segments the objects into local surface patches and uses a number of perceptual heuristics, such as highlights, shadows, and silhouettes, to enhance the perception of shape. We show our results on scientific and sculptured datasets.

We present a space leaping technique for accelerating volume rendering with very low space and run-time complexity. Our technique exploits the ray coherence during ray casting by using the distance a ray traverses in empty space to leap its neighboring rays. Our technique works with parallel as well as perspective volume rendering, does not require any preprocessing or 3D data structures, and is independent of the transfer function. Being an image-space technique, it is independent of the complexity of the data being rendered. It can be used to accelerate both time-coherent and noncoherent animation sequences.