Interactive Fusion and Tracking For Multi‐Modal Spatial Data Visualization

Scientific data acquired through sensors which monitor natural phenomena, as well as simulation data that imitate time‐identified events, have fueled the need for interactive techniques to successfully analyze and understand trends and patterns across space and time. We present a novel interactive visualization technique that fuses ground truth measurements with simulation results in real‐time to support the continuous tracking and analysis of spatiotemporal patterns. We start by constructing a reference model which densely represents the expected temporal behavior, and then use GPU parallelism to advect measurements on the model and track their location at any given point in time. Our results show that users can interactively fill the spatio‐temporal gaps in real world observations, and generate animations that accurately describe physical phenomena.     

InSpectr: Multi‐Modal Exploration,Visualization, and Analysis of Spectral Data

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.     

Flow Curves: an Intuitive Interface for Coherent Scene Deformation

Effective composition in visual arts relies on the principle of movement, where the viewer's eye is directed along subjective curves to a center of interest. We call these curves subjective because they may span the edges and/or center‐lines of multiple objects, as well as contain missing portions which are automatically filled by our visual system. By carefully coordinating the shape of objects in a scene, skilled artists direct the viewer's attention via strong subjective curves. While traditional 2D sketching is a natural fit for this task, current 3D tools are object‐centric and do not accommodate coherent deformation of multiple shapes into smooth flows. We address this shortcoming with a new sketch‐based interface called Flow Curves which allows coordinating deformation across multiple objects. Core components of our method include an understanding of the principle of flow, algorithms to automatically identify subjective curve elements that may span multiple disconnected objects, and a deformation representation tailored to the view‐dependent nature of scene movement. As demonstrated in our video, sketching flow curves requires significantly less time than using traditional 3D editing workflows.     

Exploring and Comparing Clusterings of Multivariate Data Sets Using Persistent Homology

Clustering algorithms support exploratory data analysis by grouping inputs that share similar features. Especially the clustering of unlabelled data is said to be a fiendishly difficult problem, because users not only have to choose a suitable clustering algorithm but also a suitable number of clusters. The known issues of existing clustering validity measures comprise instabilities in the presence of noise and restrictive assumptions about cluster shapes. In addition, they cannot evaluate individual clusters locally. We present a new measure for assessing and comparing different clusterings both on a global and on a local level. Our measure is based on the topological method of persistent homology, which is stable and unbiased towards cluster shapes. Based on our measure, we also describe a new visualization that displays similarities between different clusterings (using a global graph view) and supports their comparison on the individual cluster level (using a local glyph view). We demonstrate how our visualization helps detect different—but equally valid—clusterings of data sets from multiple application domains.     

Illustrative Visualization of Mesoscale Ocean Eddies

Feature‐based time‐varying volume visualization is combined with illustrative visualization to tell the story of how mesoscale ocean eddies form in the Gulf Stream and transport heat and nutrients across the ocean basin. The internal structure of these three‐dimensional eddies and the kinematics with which they move are critical to a full understanding of ocean eddies. In this work, we apply a feature‐based method to track instances of ocean eddies through the time steps of a high‐resolution multi‐decadal regional ocean model and generate a series of eddy paths which reflect the life cycle of individual eddy instances. Based on the computed metadata, several important geometric and physical properties of eddy are computed. Illustrative visualization techniques, including visual effectiveness enhancement, focus+context, and smart visibility, are combined with the extracted volume features to explore eddy characteristics at different levels. An evaluation by domain experts indicates that combining our feature‐based techniques with illustrative visualization techniques provides an insight into the role eddies play in ocean circulation. The domain experts expressed a preference for our methods over existing tools.     

Cytosplore: Interactive Immune Cell Phenotyping for Large Single‐Cell Datasets

To understand how the immune system works, one needs to have a clear picture of its cellular compositon and the cells' corresponding properties and functionality. Mass cytometry is a novel technique to determine the properties of single‐cells with unprecedented detail. This amount of detail allows for much finer differentiation but also comes at the cost of more complex analysis. In this work, we present Cytosplore, implementing an interactive workflow to analyze mass cytometry data in an integrated system, providing multiple linked views, showing different levels of detail and enabling the rapid definition of known and unknown cell types. Cytosplore handles millions of cells, each represented as a high‐dimensional data point, facilitates hypothesis generation and confirmation, and provides a significant speed up of the current workflow. We show the effectiveness of Cytosplore in a case study evaluation.     

STAR: Visual Computing in Materials Science

Visual computing has become highly attractive for boosting research endeavors in the materials science domain. Using visual computing, a multitude of different phenomena may now be studied, at various scales, dimensions, or using different modalities. This was simply impossible before. Visual computing techniques provide novel insights in order to understand complex material systems of interest, which is demonstrated by strongly rising number of new approaches, publishing new techniques for materials analysis and simulation. Outlining the proximity of materials science and visual computing, this state of the art report focuses on the intersection of both domains in order to guide research endeavors in this field. We provide a systematic survey on the close interrelations of both fields as well as how they profit from each other. Analyzing the existing body of literature, we review the domain of visual computing supported materials science, starting with the definition of materials science as well as material systems for which visual computing is frequently used. Major tasks for visual computing, visual analysis and visualization in materials sciences are identified, as well as simulation and testing techniques, which are providing the data for the respective analyses. We reviewed the input data characteristics and the direct and derived outputs, the visualization techniques and visual metaphors used, as well as the interactions and analysis workflows employed. All our findings are finally integrated in a cumulative matrix, giving insights about the different interrelations of both domains. We conclude our report with the identification of open high level and low level challenges for future research.     

Structure Aware Visual Cryptography

Visual cryptography is an encryption technique that hides a secret image by distributing it between some shared images made up of seemingly random black‐and‐white pixels. Extended visual cryptography (EVC) goes further in that the shared images instead represent meaningful binary pictures. The original approach to EVC suffered from low contrast, so later papers considered how to improve the visual quality of the results by enhancing contrast of the shared images. This work further improves the appearance of the shared images by preserving edge structures within them using a framework of dithering followed by a detail recovery operation. We are also careful to suppress noise in smooth areas.     

Persistent Homology for the Evaluation of Dimensionality Reduction Schemes

High‐dimensional data sets are a prevalent occurrence in many application domains. This data is commonly visualized using dimensionality reduction (DR) methods. DR methods provide e.g. a two‐dimensional embedding of the abstract data that retains relevant high‐dimensional characteristics such as local distances between data points. Since the amount of DR algorithms from which users may choose is steadily increasing, assessing their quality becomes more and more important. We present a novel technique to quantify and compare the quality of DR algorithms that is based on persistent homology. An inherent beneficial property of persistent homology is its robustness against noise which makes it well suited for real world data. Our pipeline informs about the best DR technique for a given data set and chosen metric (e.g. preservation of local distances) and provides knowledge about the local quality of an embedding, thereby helping users understand the shortcomings of the selected DR method. The utility of our method is demonstrated using application data from multiple domains and a variety of commonly used DR methods.     

Paint and Click: Unified Interactions for Image Boundaries

Image boundaries are a fundamental component of many interactive digital photography techniques, enabling applications such as segmentation, panoramas, and seamless image composition. Interactions for image boundaries often rely on two complementary but separate approaches: editing via painting or clicking constraints. In this work, we provide a novel, unified approach for interactive editing of pairwise image boundaries that combines the ease of painting with the direct control of constraints. Rather than a sequential coupling, this new formulation allows full use of both interactions simultaneously, giving users unprecedented flexibility for fast boundary editing. To enable this new approach, we provide technical advancements. In particular, we detail a reformulation of image boundaries as a problem of finding cycles, expanding and correcting limitations of the previous work. Our new formulation provides boundary solutions for painted regions with performance on par with state‐of‐the‐art specialized, paint‐only techniques. In addition, we provide instantaneous exploration of the boundary solution space with user constraints. Finally, we provide examples of common graphics applications impacted by our new approach.     

A randomized algorithm for natural object colorization

Natural objects often contain vivid color distribution with wide variety of colors. Conventional colorization techniques, on the other hand, produce colors that are relatively flat with little color variation. In this paper, we introduce a randomized algorithm which considers not only the value of target color but also the distribution of target color. In essence, our algorithm paints a color distribution to a region which synthesizes color distribution of a natural object. Our approach models the correlation between intensity and color in HSV color space in terms of H – S, H – V and S – V joint histogram. During the colorization process, we randomly swap and reassign color of a pixel to minimize a cost function that measures color consistency to its neighborhood and intensity‐to‐color correlation captured in the joint histogram. We tested our algorithm extensively on many natural objects and our user study confirms that our results are more vivid and natural compared to results from previous techniques.     

Automatic generation of tourist brochures

We present a novel framework for the automatic generation of tourist brochures that include routing instructions and additional information presented in the form of so‐called detail lenses. The first contribution of this paper is the automatic creation of layouts for the brochures. Our approach is based on the minimization of an energy function that combines multiple goals: positioning of the lenses as close as possible to the corresponding region shown in an overview map, keeping the number of lenses low, and an efficient numbering of the lenses. The second contribution is a route‐aware simplification of the graph of streets used for traveling between the points of interest (POIs). This is done by reducing the graph consisting of all shortest paths through the minimization of an energy function. The output is a subset of street segments that enable traveling between all the POIs without considerable detours, while at the same time guaranteeing a clutter‐free visualization.     

Comparative Blood Flow Visualization for Cerebral Aneurysm Treatment Assessment

A pathological vessel dilation in the brain, termed cerebral aneurysm, bears a high risk of rupture, and is associated with a high mortality. In recent years, incidental findings of unruptured aneurysms have become more frequent, mainly due to advances in medical imaging. The pathological condition is often treated with a stent that diverts the blood flow from the aneurysm sac back to the original vessel. Prior to treatment, neuroradiologists need to decide on the optimal stent configuration and judge the long‐term rupture risk, for which blood flow information is essential. Modern patient‐specific simulations can model the hemodynamics for various stent configurations, providing important indicators to support the decision‐making process. However, the necessary visual analysis of these data becomes tedious and time‐consuming, because of the abundance of information. We introduce a comprehensive comparative visualization that integrates morphology with blood flow indicators to facilitate treatment assessment. To deal with the visual complexity, we propose a details‐on‐demand approach, combining established medical visualization techniques with innovative glyphs inspired by information visualization concepts. In an evaluation we have obtained informal feedback from domain experts, gauging the value of our visualization.     

Exploring the Visualization Design Space with Repertory Grids

There is an ongoing discussion in the visualization community about the relevant factors that render a visualization effective, expressive, memorable, aesthetically pleasing, etc. These factors lead to a large design space for visualizations. To explore this design space, qualitative research methods based on observations and interviews are often necessary. We describe an interview method that allows us to systematically acquire and assess important factors from subjective answers by interviewees. To this end, we adopt the repertory grid methodology in the context of visualization. It is based on the personal construct theory: each personality interprets a topic based on a set of personal, basic constructs expressed as contrasts. For the individual interpretation of visualizations, this means that these personal terms can be very different, depending on numerous influences, such as the prior experiences of the interviewed person. We present an interviewing process, visual interface, and qualitative and quantitative analysis procedures that are specifically devised to fit the needs of visualization applications. A showcase interview with 15 typical static information visualizations and 10 participants demonstrates that our approach is effective in identifying common constructs as well as individual differences. In particular, we investigate differences between expert and nonexpert interviewees. Finally, we discuss the differences to other qualitative methods and how the repertory grid can be embedded in existing theoretical frameworks of visualization research for the design process.     

Visualizing the Impact of Geographical Variations on Multivariate Clustering

Traditional multivariate clustering approaches are common in many geovisualization applications. These algorithms are used to define geodemographic profiles, ecosystems and various other land use patterns that are based on multivariate measures. Cluster labels are then projected onto a choropleth map to enable analysts to explore spatial dependencies and heterogeneity within the multivariate attributes. However, local variations in the data and choices of clustering parameters can greatly impact the resultant visualization. In this work, we develop a visual analytics framework for exploring and comparing the impact of geographical variations for multivariate clustering. Our framework employs a variety of graphical configurations and summary statistics to explore the spatial extents of clustering. It also allows users to discover patterns that can be concealed by traditional global clustering via several interactive visualization techniques including a novel drag & drop clustering difference view. We demonstrate the applicability of our framework over a demographics dataset containing quick facts about counties in the continental United States and demonstrate the need for analytical tools that can enable users to explore and compare clustering results over varying geographical features and scales.     

Blue‐Noise Remeshing with Farthest Point Optimization

In this paper, we present a novel method for surface sampling and remeshing with good blue‐noise properties. Our approach is based on the farthest point optimization (FPO), a relaxation technique that generates high quality blue‐noise point sets in 2D. We propose two important generalizations of the original FPO framework: adaptive sampling and sampling on surfaces. A simple and efficient algorithm for accelerating the FPO framework is also proposed. Experimental results show that the generalized FPO generates point sets with excellent blue‐noise properties for adaptive and surface sampling. Furthermore, we demonstrate that our remeshing quality is superior to the current state‐of‐the?art approaches.     

An Interactive Design System of Free‐Formed Bamboo‐Copters

We present an interactive design system for designing free‐formed bamboo‐copters, where novices can easily design free‐formed, even asymmetric bamboo‐copters that successfully fly. The designed bamboo‐copters can be fabricated using digital fabrication equipment, such as a laser cutter. Our system provides two useful functions for facilitating this design activity. First, it visualizes a simulated flight trajectory of the current bamboo‐copter design, which is updated in real time during the user's editing. Second, it provides an optimization function that automatically tweaks the current bamboo‐copter design such that the spin quality—how stably it spins—and the flight quality—how high and long it flies—are enhanced. To enable these functions, we present non‐trivial extensions over existing techniques for designing free‐formed model airplanes [ UKSI14 ], including a wing discretization method tailored to free‐formed bamboo‐copters and an optimization scheme for achieving stable bamboo‐copters considering both spin and flight qualities.     

User‐Assisted Video Stabilization

We present a user‐assisted video stabilization algorithm that is able to stabilize challenging videos when state‐of‐the‐art automatic algorithms fail to generate a satisfactory result. Current methods do not give the user any control over the look of the final result. Users either have to accept the stabilized result as is, or discard it should the stabilization fail to generate a smooth output. Our system introduces two new modes of interaction that allow the user to improve the unsatisfactory stabilized video. First, we cluster tracks and visualize them on the warped video. The user ensures that appropriate tracks are selected by clicking on track clusters to include or exclude them. Second, the user can directly specify how regions in the output video should look by drawing quadrilaterals to select and deform parts of the frame. These user‐provided deformations reduce undesirable distortions in the video. Our algorithm then computes a stabilized video using the user‐selected tracks, while respecting the user‐modified regions. The process of interactively removing user‐identified artifacts can sometimes introduce new ones, though in most cases there is a net improvement. We demonstrate the effectiveness of our system with a variety of challenging hand held videos.