Steven Bergner

DimStiller: Workflows for dimensional analysis and reduction

DimStiller is a system for dimensionality reduction and analysis. It frames the task of understanding and transforming input dimensions as a series of analysis steps where users transform data tables by chaining together different techniques, called operators, into pipelines of expressions. The individual operators have controls and views that are linked together based on the structure of the expression. Users interact with the operator controls to tune parameter choices, with immediate visual feedback guiding the exploration of local neighborhoods of the space of possible data tables. DimStiller also provides global guidance for navigating data-table space through expression templates called workflows, which permit re-use of common patterns of analysis.

A Spectral Analysis of Function Composition and its Implications for Sampling in Direct Volume Visualization

In this paper we investigate the effects of function composition in the form g(f(x)) = h(x) by means of a spectral analysis of h. We decompose the spectral description of h(x) into a scalar product of the spectral description of g(x) and a term that solely depends on f(x) and that is independent of g(x). We then use the method of stationary phase to derive the essential maximum frequency of g(f(x)) bounding the main portion of the energy of its spectrum. This limit is the product of the maximum frequency of g(x) and the maximum derivative of f(x). This leads to a proper sampling of the composition h of the two functions g and f. We apply our theoretical results to a fundamental open problem in volume rendering - the proper sampling of the rendering integral after the application of a transfer function. In particular, we demonstrate how the sampling criterion can be incorporated in adaptive ray integration, visualization with multi-dimensional transfer functions, and pre-integrated volume rendering

ParaGlide: Interactive Parameter Space Partitioning for Computer Simulations

In this paper, we introduce ParaGlide, a visualization system designed for interactive exploration of parameter spaces of multidimensional simulation models. To get the right parameter configuration, model developers frequently have to go back and forth between setting input parameters and qualitatively judging the outcomes of their model. Current state-of-the-art tools and practices, however, fail to provide a systematic way of exploring these parameter spaces, making informed decisions about parameter configurations a tedious and workload-intensive task. ParaGlide endeavors to overcome this shortcoming by guiding data generation using a region-based user interface for parameter sampling and then dividing the models input parameter space into partitions that represent distinct output behavior. In particular, we found that parameter space partitioning can help model developers to better understand qualitative differences among possibly high-dimensional model outputs. Further, it provides information on parameter sensitivity and facilitates comparison of models. We developed ParaGlide in close collaboration with experts from three different domains, who all were involved in developing new models for their domain. We first analyzed current practices of six domain experts and derived a set of tasks and design requirements, then engaged in a user-centered design process, and finally conducted three longitudinal in-depth case studies underlining the usefulness of our approach.

A tool to create illuminant and reflectance spectra for light-driven graphics and visualization

Full spectra allow the generation of a physically correct rendering of a scene under different lighting conditions. In this article we devise a tool to augment a palette of given lights and material reflectances with constructed spectra, yielding specified colors or spectral properties such as metamerism or objective color constancy. We utilize this to emphasize or hide parts of a scene by matching or differentiating colors under different illuminations. These color criteria are expressed as a quadratic programming problem, which may be solved with positivity constraints. Further, we characterize full spectra of lights, surfaces, and transmissive materials in an efficient linear subspace model by forming eigenvectors of sets of spectra and transform them to an intermediate space in which spectral interactions reduce to simple component-wise multiplications during rendering. The proposed method enhances the users freedom in designing photo-realistic scenes and helps in creating expressive visualizations. A key application of our technique is to use specific spectral lighting to scale the visual complexity of a scene by controlling visibility of texture details in surface graphics or material details in volume rendering.

A granular three dimensional multiresolution transform

We propose a three dimensional multi-resolution scheme to represent volumetric data in resolutions which are powers of two, resolving the rigidity of the commonly used separable Cartesian multi-resolution schemes in 3D that only allow for change of resolution by a power of eight. Through in-depth comparisons with the counterpart resampling solutions on the Cartesian lattice, we demonstrate the superiority of our subsampling scheme. We derive and document the Fourier domain analysis of this representation. Using such an analysis one can obtain ideal and discrete multidimensional filters for this multi-resolution scheme.

A mixing board interface for graphics and visualization applications

We use a haptically enhanced mixing board with a video projector as an interface to various data visualization tasks. We report results of an expert review with four participants, qualitatively evaluating the board for three different applications: dynamic queries (abstract task), parallel coordinates interface (multi-dimensional combinatorial search), and ExoVis (3D spatial navigation). Our investigation sought to determine the strengths of this physical input given its capability to facilitate bimanual interaction, constraint maintenance, tight coupling of input and output, and other features. Participants generally had little difficulty with the mappings of parameters to sliders. The graspable sliders apparently reduced the mental exertion needed to acquire control, allowing participants to attend more directly to understanding the visualization. Participants often designated specific roles for each hand, but only rarely moved both hands simultaneously.

Interactive spectral volume rendering

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.

Deformable structural models

A hierarchical framework for the recognition of complex deformable shapes is developed. In extension to traditional approaches an additional layer of control is introduced to guide the local search for subshapes. This is realized by incorporating knowledge about their spatial relationships. A new technique of expectation maps is applied to allow simultaneous shape searches to influence each other. Furthermore, these maps are used to assess spatial coherence among shapes. Thus, the occurrence of well matched shapes at some places in the image may suggest searches for related shapes at other positions. An application to classify species in ant image databases shows promising initial results.

THE MIRA–TITAN UNIVERSE: PRECISION PREDICTIONS FOR DARK ENERGY SURVEYS

Ground and space-based sky surveys enable powerful cosmological probes based on measurements of galaxy properties and the distribution of galaxies in the Universe. These probes include weak lensing, baryon acoustic oscillations, abundance of galaxy clusters, and redshift space distortions; they are essential to improving our knowledge of the nature of dark energy. On the theory and modeling front, large-scale simulations of cosmic structure formation play an important role in interpreting the observations and in the challenging task of extracting cosmological physics at the needed precision. These simulations must cover a parameter range beyond the standard six cosmological parameters and need to be run at high mass and force resolution. One key simulation-based task is the generation of accurate theoretical predictions for observables, via the method of emulation. Using a new sampling technique, we explore an 8-dimensional parameter space including massive neutrinos and a variable dark energy equation of state. We construct trial emulators using two surrogate models (the linear power spectrum and an approximate halo mass function). The new sampling method allows us to build precision emulators from just 26 cosmological models and to increase the emulator accuracy by adding new sets of simulations in a prescribed way. This allows emulator fidelity to be systematically improved as new observational data becomes available and higher accuracy is required. Finally, using one LCDM cosmology as an example, we study the demands imposed on a simulation campaign to achieve the required statistics and accuracy when building emulators for dark energy investigations.

Spatio-chromatic decorrelation for color image compression

We investigate the implications of a unified spatio-chromatic basis for image compression and reconstruction. Different adaptive and general methods (principal component analysis, PCA, independent component analysis, ICA, and discrete cosine transform, DCT) are applied to generate bases. While typically such bases with spatial extent are investigated in terms of their correspondence to human visual perception, we are interested in their applicability to multimedia encoding. The performance of the extracted spatio-chromatic spatial patch bases is evaluated in terms of quality of reconstruction with respect to their potential for data compression. Since ICA is not as widely used as it should be, compared to the other decorrelation methods applied here in a new domain, we also provide a review of ICA. The results discussed here are intended to provide another path towards perceptually based encoding of visual data. This leads to a deeper understanding of the role played by chromatic features in data reduction.