GraSp: Combining Spatially‐aware Mobile Devices and a Display Wall for Graph Visualization and Interaction

Going beyond established desktop interfaces, researchers have begun re‐thinking visualization approaches to make use of alternative display environments and more natural interaction modalities. In this paper, we investigate how spatially‐aware mobile displays and a large display wall can be coupled to support graph visualization and interaction. For that purpose, we distribute typical visualization views of classic node‐link and matrix representations between displays. The focus of our work lies in novel interaction techniques that enable users to work with personal mobile devices in combination with the wall. We devised and implemented a comprehensive interaction repertoire that supports basic and advanced graph exploration and manipulation tasks, including selection, details‐on‐demand, focus transitions, interactive lenses, and data editing. A qualitative study has been conducted to identify strengths and weaknesses of our techniques. Feedback showed that combining mobile devices and a wall‐sized display is useful for diverse graph‐related tasks. We also gained valuable insights regarding the distribution of visualization views and interactive tools among the combined displays.     

The Undistort Lens

Detail‐in‐context lens techniques can be useful for exploring visualizations of data spaces that are too large or have too much detail to fit in regular displays. For example, by bending the space in the right way we can bring together details from two separate areas for easy comparison while roughly keeping the context that situates each area within the global space. While these techniques can be powerful tools, they also introduce distortions that need to be understood, and often the tools have to be disabled in order to have access to the undistorted data. We introduce the undistort lens, a complement to existing distortion‐based techniques that provides a local and separate presentation of the original geometry without affecting any distortion‐based lenses currently used in the presentation. The undistort lens is designed to allow interactive access to the underlying undistorted data within the context of the distorted space, and to enable a better understanding of the distortions. The paper describes the implementation of a generic back‐mapping mechanism that enables the implementation of undistort lenses for arbitrary distortion based techniques, including those presented in the lens literature. We also provide a series of use‐case scenarios that demonstrate the situations in which the technique can complement existing lenses.     

Using Wavefront Tracing for the Visualization and Optimization of Progressive Lenses

Progressive addition lenses are a relatively new approach to compensate for defects of the human visual system. While traditional spectacles use rotationally symmetric lenses, progressive lenses require the specification of free-form surfaces. This poses difficult problems for the optimal design and its visual evaluation.
This paper presents two new techniques for the visualization of optical systems and the optimization of progressive lenses. Both are based on the same wavefront tracing approach to accurately evaluate the refraction properties of complex optical systems.
We use the results of wavefront tracing for continuously re-focusing the eye during rendering. Together with distribution ray tracing, this yields high-quality images that accurately simulate the visual quality of an optical system. The design of progressive lenses is difficult due to the trade-off between the desired properties of the lens and unavoidable optical errors, such as astigmatism and distortions. We use wavefront tracing to derive an accurate error functional describing the desired properties and the optical error across a lens. Minimizing this error yields optimal free-form lens surfaces.
While the basic approach is much more general, in this paper, we describe its application to the particular problem of designing and evaluating progressive lenses and demonstrate the benefits of the new approach with several example images.     

Route Visualization Using Detail Lenses

We present a method designed to address some limitations of typical route map displays of driving directions. The main goal of our system is to generate a printable version of a route map that shows the overview and detail views of the route within a single, consistent visual frame. Our proposed visualization provides a more intuitive spatial context than a simple list of turns. We present a novel multifocus technique to achieve this goal, where the foci are defined by points of interest (POI) along the route. A detail lens that encapsulates the POI at a finer geospatial scale is created for each focus. The lenses are laid out on the map to avoid occlusion with the route and each other, and to optimally utilize the free space around the route. We define a set of layout metrics to evaluate the quality of a lens layout for a given route map visualization. We compare standard lens layout methods to our proposed method and demonstrate the effectiveness of our method in generating aesthetically pleasing layouts. Finally, we perform a user study to evaluate the effectiveness of our layout choices.     

A flexible multi-volume shader framework for arbitrarily intersecting multi-resolution datasets

We present a powerful framework for 3D-texture-based rendering of multiple arbitrarily intersecting volumetric datasets. Each volume is represented by a multi-resolution octree-based structure and we use out-of-core techniques to support extremely large volumes. Users define a set of convex polyhedral volume lenses, which may be associated with one or more volumetric datasets. The volumes or the lenses can be interactively moved around while the region inside each lens is rendered using interactively defined multi-volume shaders. Our rendering pipeline splits each lens into multiple convex regions such that each region is homogenous and contains a fixed number of volumes. Each such region is further split by the brick boundaries of the associated octree representations. The resulting puzzle of lens fragments is sorted in front-to-back or back-to-front order using a combination of a view-dependent octree traversal and a GPU-based depth peeling technique. Our current implementation uses slice-based volume rendering and allows interactive roaming through multiple intersecting multi-gigabyte volumes.     

A Time Model for Time-Varying Visualization

The analysis of unsteady phenomena is an important topic for scientific visualization. Several time-dependent visualization techniques exist, as well as solutions for dealing with the enormous size of time-varying data in interactive visualization. Many current visualization toolkits support displaying time-varying data sets. However, for the interactive exploration of time-varying data in scientific visualization, no common time model that describes the temporal properties which occur in the visualization process has been established. In this work, we propose a general time model which classifies the time frames of simulation phenomena and the connections between different time scales in the analysis process. This model is designed for intuitive interaction with time in visualization applications for the domain expert as well as for the developer of visualization tools. We demonstrate the benefits of our model by applying it to two use cases with different temporal properties.     

The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations

Machine learning (ML) models are nowadays used in complex applications in various domains, such as medicine, bioinformatics, and other sciences. Due to their black box nature, however, it may sometimes be hard to understand and trust the results they provide. This has increased the demand for reliable visualization tools related to enhancing trust in ML models, which has become a prominent topic of research in the visualization community over the past decades. To provide an overview and present the frontiers of current research on the topic, we present a State-of-the-Art Report (STAR) on enhancing trust in ML models with the use of interactive visualization. We define and describe the background of the topic, introduce a categorization for visualization techniques that aim to accomplish this goal, and discuss insights and opportunities for future research directions. Among our contributions is a categorization of trust against different facets of interactive ML, expanded and improved from previous research. Our results are investigated from different analytical perspectives: (a) providing a statistical overview, (b) summarizing key findings, (c) performing topic analyses, and (d) exploring the data sets used in the individual papers, all with the support of an interactive web-based survey browser. We intend this survey to be beneficial for visualization researchers whose interests involve making ML models more trustworthy, as well as researchers and practitioners from other disciplines in their search for effective visualization techniques suitable for solving their tasks with confidence and conveying meaning to their data.     

Pathline glyphs

Visualization of pathlines is common and highly relevant for the analysis of unsteady flow. However, pathlines can intersect, leading to visual clutter and perceptual issues. This makes it intrinsically difficult to provide expressive visualizations of the entire domain by an arrangement of multiple pathlines, in contrast to well‐established streamline placement techniques. We present an approach to reduce these problems. It is inspired by glyph‐based visualization and small multiples: we partition the domain into cells, each corresponding to a downscaled version of the entire domain. Inside these cells, a single downscaled pathline is drawn. On the overview scale, our pathline glyphs lead to emergent visual patterns that provide insight into time‐dependent flow behavior. Zooming‐in allows us to analyze individual pathlines in detail and compare neighboring lines. The overall approach is complemented with a context‐preserving zoom lens and interactive pathline‐based exploration. While we primarily target the visualization of 2D flow, we also address the extension to 3D. Our evaluation includes several examples, comparison to other flow visualization techniques, and a user study with domain experts.     

Interactive visual analysis of set-typed data

While it is quite typical to deal with attributes of different data types in the visualization of heterogeneous and multivariate datasets, most existing techniques still focus on the most usual data types such as numerical attributes or strings. In this paper we present a new approach to the interactive visual exploration and analysis of data that contains attributes which are of set type. A set-typed attribute of a data item--like one cell in a table--has a list of n > or = 0 elements as its value. We present the set'o'gram as a new visualization approach to represent data of set type and to enable interactive visual exploration and analysis. We also demonstrate how this approach is capable to help in dealing with datasets that have a larger number of dimensions (more than a dozen or more), especially also in the context of categorical data. To illustrate the effectiveness of our approach, we present the interactive visual analysis of a CRM dataset with data from a questionnaire on the education and shopping habits of about 90000 people.     

Automatic Animation for Time‐Varying Data Visualization

This paper presents a digital storytelling approach that generates automatic animations for time‐varying data visualization. Our approach simulates the composition and transition of storytelling techniques and synthesizes animations to describe various event features. Specifically, we analyze information related to a given event and abstract it as an event graph, which represents data features as nodes and event relationships as links. This graph embeds a tree‐like hierarchical structure which encodes data features at different scales. Next, narrative structures are built by exploring starting nodes and suitable search strategies in this graph. Different stages of narrative structures are considered in our automatic rendering parameter decision process to generate animations as digital stories. We integrate this animation generation approach into an interactive exploration process of time‐varying data, so that more comprehensive information can be provided in a timely fashion. We demonstrate with a storm surge application that our approach allows semantic visualization of time‐varying data and easy animation generation for users without special knowledge about the underlying visualization techniques.     

GTMapLens: Interactive Lens for Geo-Text Data Browsing on Map

Data containing geospatial semantics, such as geotagged tweets, travel blogs, and crime reports, associates natural language texts with geographical locations. This paper presents a lens-based visual interaction technique, GTMapLens, to flexibly browse the geo-text data on a map. It allows users to perform dynamic focus+context exploration by using movable lenses to browse geographical regions, find locations of interest, and perform comparative and drill-down studies. Geo-text data is visualized in a way that users can easily perceive the underlying geospatial semantics along with lens moving. Based on a requirement analysis with a cohort of multidisciplinary domain experts, a set of lens interaction techniques are developed including keywords control, path management, context visualization, and snapshot anchors. They allow users to achieve a guided and controllable exploration of geo-text data. A hierarchical data model enables the interactive lens operations by accelerated data retrieval from a geo-text database. Evaluation with real-world datasets is presented to show the usability and effectiveness of GTMapLens.     

An Eyeglass Simulator Using Conoid Tracing

This paper proposes a method for displaying images at the fovea of the retina taking visual acuity into account. Previous research has shown that a point light source projected onto the retina forms an ellipse, which can be computed with wavefront tracing from each point in space. We propose a novel concept using conoid tracing, with which we can acquire defocusing information several times faster than that acquired by previous methods. We also show that conoid tracing is more robust and produces higher quality results. In conoid tracing the ray is regarded as a conoid, a thin cone‐like shape with varying elliptical cross‐section. The viewing ray from the retina is traced as a conoid and evaluated at each sample location. Using the sampled and pre‐computed data for the spatial distribution of blurring, we implemented an interactive eyeglass simulator. This paper demonstrates some visualization results utilizing the interactivity of the simulator, which an eyeglass lens design company uses to evaluate the design of complex progressive lenses.     

Countering security information overload through alert and packet visualization

This article presents a framework for designing network security visualization systems as well as results from the end-to-end design and implementation of two highly interactive systems. In this article, we provide multiple contributions: we present the results of our survey of security professionals, the design framework, and lessons learned from the design of our systems as well as an evaluation of their effectiveness. Our results indicate that both systems effectively present significantly more information when compared to traditional textual approaches. We believe that the interactive, graphical techniques that we present will have broad applications in other domains seeking to deal with information overload.     

Straightening tubular flow for side-by-side visualization

Flows through tubular structures are common in many fields, including blood flow in medicine and tubular fluid flows in engineering. The analysis of such flows is often done with a strong reference to the main flow direction along the tubular boundary. In this paper we present an approach for straightening the visualization of tubular flow. By aligning the main reference direction of the flow, i.e., the center line of the bounding tubular structure, with one axis of the screen, we are able to natively juxtapose (1.) different visualizations of the same flow, either utilizing different flow visualization techniques, or by varying parameters of a chosen approach such as the choice of seeding locations for integration-based flow visualization, (2.) the different time steps of a time-dependent flow, (3.) different projections around the center line , and (4.) quantitative flow visualizations in immediate spatial relation to the more qualitative classical flow visualization. We describe how to utilize this approach for an informative interactive visual analysis. We demonstrate the potential of our approach by visualizing two datasets from two different fields: an arterial blood flow measurement and a tubular gas flow simulation from the automotive industry.     

RETRACTED ARTICLE: Texture-guided volumetric deformation and visualization using 3D moving least squares

Examining and manipulating the large volumetric data attract great interest for various applications. For such purpose, we first extend the 2D moving least squares (MLS) technique into 3D, and propose a texture-guided deformation technique for creating visualization styles through interactive manipulations of volumetric models using 3D MLS. Our framework includes focus+context (F+C) visualization for simultaneously showing the entire model after magnification, and the cut-away or illustrative visualization for providing a better understanding of anatomical and biological structures. Both visualization styles are widely applied in the graphics areas. We present a mechanism for defining features using high-dimensional texture information, and design an interface for visualizing, selecting and extracting features/objects of interest. Methods of the interactive or automatic generation of 3D control points are proposed for the flexible and plausible deformation. We describe a GPU-based implementation to achieve real-time performance of the deformation techniques and the manipulation operators. Different from physical deformation models, our framework is goal-oriented and user-guided. We demonstrate the robustness and efficiency of our framework using various volumetric datasets.     

Detailed 3D reconstruction of large-scale heritage sites with integrated techniques

Many cultural heritage applications require 3D reconstruction of real-world objects and scenes. Over the past few years, it has become increasingly common to use 3D digitization and modeling for this purpose. This is mainly due to advances in laser-scanning techniques, 3D modeling software, image-based modeling techniques, computer power, and virtual reality. Our approach integrates several technologies based on our experience over more than a decade of trying to accurately and completely model large-scale heritage monuments and sites. Using both interactive and automatic techniques, we can model a highly detailed structure or site at various levels of detail. We use image-based modeling for basic shape and structural elements, and laser scanning for fine details and sculpted surfaces. To present the site in its proper context, we use image-based rendering for landscapes and surroundings. To apply this approach, we created hundreds of models from sites all over the world for documentation, walk-through movies, and interactive visualization. The results were compelling and encouraging.     

Visualizing multiwavelength astrophysical data

With recent advances in the measurement technology for allsky astrophysical imaging, our view of the sky is no longer limited to the tiny visible spectral range over the 2D Celestial sphere. We now can access a third dimension corresponding to a broad electromagnetic spectrum with a wide range of allsky surveys; these surveys span frequency bands including long wavelength radio, microwaves, very short X-rays, and gamma rays. These advances motivate us to study and examine multiwavelength visualization techniques to maximize our capabilities to visualize and exploit these informative image data sets. In this work, we begin with the processing of the data themselves, uniformizing the representations and units of raw data obtained from varied detector sources. Then we apply tools to map, convert, color-code, and format the multiwavelength data in forms useful for applications. We explore different visual representations for displaying the data, including such methods as textured image stacks, the horseshoe representation, and GPU-based volume visualization. A family of visual tools and analysis methods is introduced to explore the data, including interactive data mapping on the graphics processing unit (GPU), the mini-map explorer, and GPU-based interactive feature analysis.     

Feature aligned volume manipulation for illustration and visualization

In this paper we describe a GPU-based technique for creating illustrative visualization through interactive manipulation of volumetric models. It is partly inspired by medical illustrations, where it is common to depict cuts and deformation in order to provide a better understanding of anatomical and biological structures or surgical processes, and partly motivated by the need for a real-time solution that supports the specification and visualization of such illustrative manipulation. We propose two new feature-aligned techniques, namely surface alignment and segment alignment, and compare them with the axis-aligned techniques which was reported in previous work on volume manipulation. We also present a mechanism for defining features using texture volumes, and methods for computing correct normals for the deformed volume in respect to different alignments. We describe a GPU-based implementation to achieve real-time performance of the techniques and a collection of manipulation operators including peelers, retractors, pliers and dilators which are adaptations of the metaphors and tools used in surgical procedures and medical illustrations. Our approach is directly applicable in medical and biological illustration, and we demonstrate how it works as an interactive tool for focus+context visualization, as well as a generic technique for volume graphics.     

Volume-based large dynamic graph analysis supported by evolution provenance

We present an approach for the visualization and interactive analysis of dynamic graphs that contain a large number of time steps. A specific focus is put on the support of analyzing temporal aspects in the data. Central to our approach is a static, volumetric representation of the dynamic graph based on the concept of space-time cubes that we create by stacking the adjacency matrices of all time steps. The use of GPU-accelerated volume rendering techniques allows us to render this representation interactively. We identified four classes of analytics methods as being important for the analysis of large and complex graph data, which we discuss in detail: data views, aggregation and filtering, comparison, and evolution provenance. Implementations of the respective methods are presented in an integrated application, enabling interactive exploration and analysis of large graphs. We demonstrate the applicability, usefulness, and scalability of our approach by presenting two examples for analyzing dynamic graphs. Furthermore, we let visualization experts evaluate our analytics approach.

     

Degradation of iris recognition performance due to non-cosmetic prescription contact lenses

Many iris recognition systems operate under the assumption that non-cosmetic contact lenses have no or minimal effect on iris biometrics performance and convenience. In this paper we show results of a study of 12,003 images from 87 contact-lens-wearing subjects and 9697 images from 124 non-contact-lens-wearing subjects. We visually classified the contact lens images into four categories according to the type of lens effects observed in the image. Our results show different degradations in performance for different types of contact lenses. Lenses that produce larger artifacts on the iris yield more degraded performance. This is the first study to document degraded iris biometrics performance with non-cosmetic contact lenses.