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We propose an interactive web‐based application to inform the general public about personal flood risks. Flooding is the natural hazard affecting most people worldwide. Protection against flooding is not limited to mitigation measures, but also includes communicating its risks to affected individuals to raise awareness and preparedness for its adverse effects. Until now, this is mostly done with static and indiscriminate 2D maps of the water depth. These flood hazard maps can be difficult to interpret and the user has to derive a personal flood risk based on prior knowledge. In addition to the hazard, the flood risk has to consider the exposure of the own house and premises to high water depths and flow velocities as well as the vulnerability of particular parts. Our application is centered around an interactive personalized visualization to raise awareness of these risk factors for an object of interest. We carefully extract and show only the relevant information from large precomputed flood simulation and geospatial data to keep the visualization simple and comprehensible. To achieve this goal, we extend various existing approaches and combine them with new real‐time visualization and interaction techniques in 3D. A new view‐dependent focus+context design guides user attention and supports an intuitive interpretation of the visualization to perform predefined exploration tasks. HORA 3D enables users to individually inform themselves about their flood risks. We evaluated the user experience through a broad online survey with 87 participants of different levels of expertise, who rated the helpfulness of the application with 4.7 out of 5 on average. [ABSTRACT FROM AUTHOR]

High‐resolution electron microscopy imaging allows neuroscientists to reconstruct not just entire cells but individual cell substructures (i.e., cell organelles) as well. Based on these data, scientists hope to get a better understanding of brain function and development through detailed analysis of local organelle neighborhoods. In‐depth analyses require efficient and scalable comparison of a varying number of cell organelles, ranging from two to hundreds of local spatial neighborhoods. Scientists need to be able to analyze the 3D morphologies of organelles, their spatial distributions and distances, and their spatial correlations. We have designed Barrio as a configurable framework that scientists can adjust to their preferred workflow, visualizations, and supported user interactions for their specific tasks and domain questions. Furthermore, Barrio provides a scalable comparative visualization approach for spatial neighborhoods that automatically adjusts visualizations based on the number of structures to be compared. Barrio supports small multiples of spatial 3D views as well as abstract quantitative views, and arranges them in linked and juxtaposed views. To adapt to new domain‐specific analysis scenarios, we allow the definition of individualized visualizations and their parameters for each analysis session. We present an in‐depth case study for mitochondria analysis in neuronal tissue and demonstrate the usefulness of Barrio in a qualitative user study with neuroscientists. [ABSTRACT FROM AUTHOR]

In the literature on optimal regular volume sampling, the Body-Centered Cubic (BCC) lattice has been proven to be optimal for sampling spherically band-limited signals above the Nyquist limit. On the other hand, if the sampling frequency is below the Nyquist limit, the Face-Centered Cubic (FCC) lattice was demonstrated to be optimal in reducing the prealiasing effect. In this paper, we confirm that the FCC lattice is indeed optimal in this sense in a certain interval of the sampling frequency. By theoretically estimating the prealiasing error in a realistic range of the sampling frequency, we show that in other frequency intervals, the BCC lattice and even the traditional Cartesian Cubic (CC) lattice are expected to minimize the prealiasing. The BCC lattice is superior over the FCC lattice if the sampling frequency is not significantly below the Nyquist limit. Interestingly, if the original signal is drastically undersampled, the CC lattice is expected to provide the lowest prealiasing error. Additionally, we give a comprehensible clarification that the sampling efficiency of the FCC lattice is lower than that of the BCC lattice. Although this is a well-known fact, the exact percentage has been erroneously reported in the literature. Furthermore, for the sake of an unbiased comparison, we propose to rotate the Marschner-Lobb test signal such that an undue advantage is not given to either lattice. [ABSTRACT FROM AUTHOR]

This paper addresses the increasing demand in industry for methods to analyze and visualize multimodal data involving a spectral modality. Two data modalities are used: high-resolution X-ray computed tomography (XCT) for structural characterization and low-resolution X-ray fluorescence (XRF) spectral data for elemental decomposition. We present InSpectr, an integrated tool for the interactive exploration and visual analysis of multimodal, multiscalar data. The tool has been designed around a set of tasks identified by domain experts in the fields of XCT and XRF. It supports registered single scalar and spectral datasets optionally coupled with element maps and reference spectra. InSpectr is instantiating various linked views for the integration of spatial and non-spatial information to provide insight into an industrial component's structural and material composition: views with volume renderings of composite and individual 3D element maps visualize global material composition; transfer functions defined directly on the spectral data and overlaid pie-chart glyphs show elemental composition in 2D slice-views; a representative aggregated spectrum and spectra density histograms are introduced to provide a global overview in the spectral view. Spectral magic lenses, spectrum probing and elemental composition probing of points using a pie-chart view and a periodic table view aid the local material composition analysis. Two datasets are investigated to outline the usefulness of the presented techniques: a 3D virtually created phantom with a brass metal alloy and a real-world 2D water phantom with insertions of gold, barium, and gadolinium. Additionally a detailed user evaluation of the results is provided. [ABSTRACT FROM AUTHOR]

Displaying a large number of lines within a limited amount of screen space is a task that is common to many different classes of visualization techniques such as time-series visualizations, parallel coordinates, link-node diagrams, and phase-space diagrams. This paper addresses the challenging problems of cluttering and overdraw inherent to such visualizations. We generate a 2×2 tensor field during line rasterization that encodes the distribution of line orientations through each image pixel. Anisotropic diffusion of a noise texture is then used to generate a dense, coherent visualization of line orientation. In order to represent features of different scales, we employ a multi-resolution representation of the tensor field. The resulting technique can easily be applied to a wide variety of line-based visualizations. We demonstrate this for parallel coordinates, a time-series visualization, and a phase-space diagram. Furthermore, we demonstrate how to integrate a focus+context approach by incorporating a second tensor field. Our approach achieves interactive rendering performance for large data sets containing millions of data items, due to its image-based nature and ease of implementation on GPUs. Simulation results from computational fluid dynamics are used to evaluate the performance and usefulness of the proposed method. [ABSTRACT FROM AUTHOR]

Maximum Intensity Projection (MIP) is a volume rendering technique which is used to visualize high-intensity structures within volumetric data. At each pixel the highest data value, which is encountered along a corresponding viewing ray is depicted. MIP is, for example, commonly used to extract vascular structures from medical data sets (angiography). Due to lack of depth information in MIP images, animation or interactive variation of viewing parameters is frequently used for investigation. Up to now no MIP algorithms exist which are of both interactive speed and high quality. In this paper we present a high-quality MIP algorithm (trilinear interpolation within cells), which is up to 50 times faster than brute-force MIP and at least 20 times faster than comparable optimized techniques. This speed-up is accomplished by using an alternative storage scheme for volume cells (sorted by value) and by removing cells which do not contribute to any MIP projection (regardless of the viewing direction) in a preprocessing step. Also, a fast maximum estimation within cells is used to further speed up the algorithm. [ABSTRACT FROM AUTHOR]

In this paper a new gradient estimation method is presented which is based on linear regression. Previous contextual shading techniques try to fit an approximate function to a set of surface points in the neighborhood of a given voxel. Therefore a system of linear equations has to be solved using the computationally expensive Gaussian elimination. In contrast, our method approximates the density function itself in a local neighborhood with a 3D regression hyperplane. This approach also leads to a system of linear equations but we will show that it can be solved with an efficient convolution. Our method provides at each voxel location the normal vector and the translation of the regression hyperplane which are considered as a gradient and a filtered density value respectively. Therefore this technique can be used for surface smoothing and gradient estimation at the same time. [ABSTRACT FROM AUTHOR]

This paper discusses an extended camera model for ray tracing. As an alternative to standard camera modules an abstract camera machine is presented. It represents a framework of extended cameras which is based on standard mapping functions. They are integrated within the abstract camera machine to complete the camera function, which generates rays out of image locations (pixels). Modelling the camera function as an abstract camera machine in combination with standard mapping functions opens a wide field of applications and the specification of extended cameras is greatly simplified. By using extended cameras it is easily possible to produce special and artistic effects, e.g. a local non-linear zoom of especially interesting regions while still retaining an overview of the whole scene. Overviews of given scenes can be modelled and several views of the same object can be integrated into one picture. Several examples of extended cameras designed with the abstract camera machine are discussed and colour plates made with these cameras are presented. [ABSTRACT FROM AUTHOR]

A list of colleagues and international experts in the field of computer graphics who contributed to the writing of the journal is presented, including Pere Brunett, Dieter Fellner and Philip Dutre.

An introduction to the journal is presented in which the editors announce the appointment of new associate editors of the journal from April 2010 to March 2013, including Paolo Cignoni and Hans Hagen, the large number of article submissions received by the journal in 2009 and the end of the second term of Roberto Scopigno as chief editor of the journal.

The article presents information on the March 2009 issue of the periodical "Computer Graphics forum."

In this paper we present a fast visualization technique for volumetric data, which is based on a recent non-photorealistic rendering technique. Our new approach enables alternative insights into 3D data sets (compared to traditional approaches such as direct volume rendering or iso-surface rendering). Object contours, which usually are characterized by locally high gradient values, are visualized regardless of their density values. Cumbersome tuning of transfer functions, as usually needed for setting up DVR views is avoided. Instead, a small number of parameters is available to adjust the non-photorealistic display. Based on the magnitude of local gradient information as well as on the angle between viewing direction and gradient vector, data values are mapped to visual properties (color, opacity), which then are combined to form the rendered image (MIP is proposed as the default compositing stragtegy here). Due to the fast implementation of this alternative rendering approach, it is possible to interactively investigate the 3D data, and quickly learn about internal structures. Several further extensions of our new approach, such as level lines are also presented in this paper. [ABSTRACT FROM AUTHOR]