DevLan/vispubs huggingface dataset:
Visualizing the History of Living Spaces
Authors: Yuri A. Ivanov, Christopher Richard Wren, Alexander Sorokin, Ishwinder Kaur
Published at InfoVis, 2007

The technology available to building designers now makes it possible to monitor buildings on a very large scale. Video cameras and motion sensors are commonplace in practically every office space, and are slowly making their way into living spaces. The application of such technologies, in particular video cameras, while improving security, also violates privacy. On the other hand, motion sensors, while being privacy-conscious, typically do not provide enough information for a human operator to maintain the same degree of awareness about the space that can be achieved by using video cameras. We propose a novel approach in which we use a large number of simple motion sensors and a small set of video cameras to monitor a large office space. In our system we deployed 215 motion sensors and six video cameras to monitor the 3,000-square-meter office space occupied by 80 people for a period of about one year. The main problem in operating such systems is finding a way to present this highly multidimensional data, which includes both spatial and temporal components, to a human operator to allow browsing and searching recorded data in an efficient and intuitive way. In this paper we present our experiences and the solutions that we have developed in the course of our work on the system. We consider this work to be the first step in helping designers and managers of building systems gain access to information about occupants' behavior in the context of an entire building in a way that is only minimally intrusive to the occupants' privacy.
Weaving Versus Blending: a quantitative assessment of the information carrying capacities of two alternative methods for conveying multivariate data with color.
Authors: Haleh Hagh-Shenas, Sunghee Kim, Victoria Interrante, Christopher G. Healey
Published at InfoVis, 2007

In many applications, it is important to understand the individual values of, and relationships between, multiple related scalar variables defined across a common domain. Several approaches have been proposed for representing data in these situations. In this paper we focus on strategies for the visualization of multivariate data that rely on color mixing. In particular, through a series of controlled observer experiments, we seek to establish a fundamental understanding of the information-carrying capacities of two alternative methods for encoding multivariate information using color: color blending and color weaving. We begin with a baseline experiment in which we assess participants' abilities to accurately read numerical data encoded in six different basic color scales defined in the L*a*b* color space. We then assess participants' abilities to read combinations of 2, 3, 4 and 6 different data values represented in a common region of the domain, encoded using either color blending or color weaving. In color blending a single mixed color is formed via linear combination of the individual values in L*a*b* space, and in color weaving the original individual colors are displayed side-by-side in a high frequency texture that fills the region. A third experiment was conducted to clarify some of the trends regarding the color contrast and its effect on the magnitude of the error that was observed in the second experiment. The results indicate that when the component colors are represented side-by-side in a high frequency texture, most participants' abilities to infer the values of individual components are significantly improved, relative to when the colors are blended. Participants' performance was significantly better with color weaving particularly when more than 2 colors were used, and even when the individual colors subtended only 3 minutes of visual angle in the texture. However, the information-carrying capacity of the color weaving approach has its limits. We found that participants' abilities to accurately interpret each of the individual components in a high frequency color texture typically falls off as the number of components increases from 4 to 6. We found no significant advantages, in either color blending or color weaving, to using color scales based on component hues thatare more widely separated in the L*a*b* color space. Furthermore, we found some indications that extra difficulties may arise when opponent hues are employed.
A Tri-Space Visualization Interface for Analyzing Time-Varying Multivariate Volume Data
Authors: Hiroshi Akiba, Kwan-Liu Ma
Published at EuroVis, 2007

The dataset generated by a large-scale numerical simulation may include thousands of timesteps and hundreds of variables describing different aspects of the modeled physical phenomena. In order to analyze and understand such data, scientists need the capability to explore simultaneously in the temporal, spatial, and variable domains of the data. Such capability, however, is not generally provided by conventional visualization tools. This paper presents a new visualization interface addressing this problem. The interface consists of three components which abstracts the complexity of exploring in temporal, variable, and spatial domain, respectively. The first component displays time histograms of the data, helps the user identify timesteps of interest, and also helps specify time-varying features. The second component displays correlations between variables in parallel coordinates and enables the user to verify those correlations and possibly identity unanticipated ones. The third component allows the user to more closely explore and validate the data in spatial domain while rendering multiple variables into a single visualization in a user controllable fashion. Each of these three components is not only an interface but is also the visualization itself, thus enabling efficient screen-space usage. The three components are tightly linked to facilitate tri-space data exploration, which offers scientists new power to study their time-varying, multivariate volume data.
Animation of Orthogonal Texture-Based Vector Field Visualization
Authors: Sven Bachthaler, Daniel Weiskopf
Published at EuroVis, 2007

This paper introduces orthogonal vector field visualization on 2D manifolds: a representation by lines that are perpendicular to the input vector field. Line patterns are generated by line integral convolution (LIC). This visualization is combined with animation based on motion along the vector field. This decoupling of the line direction from the direction of animation allows us to choose the spatial frequencies along the direction of motion independently from the length scales along the LIC line patterns. Vision research indicates that local motion detectors are tuned to certain spatial frequencies of textures, and the above decoupling enables us to generate spatial frequencies optimized for motion perception. In addition, a filtering process is described to achieve a consistent and temporally coherent animation of the orthogonal vector field visualization. We present respective visualization algorithms for 2D planar vector fields and tangential vector fields on curved surfaces, and demonstrate that those algorithms lend themselves to efficient and interactive GPU implementations.
Depth Cues and Density in Temporal Parallel Coordinates
Authors: Jimmy Johansson 0001, Patric Ljung, Matthew Cooper 0001
Published at EuroVis, 2007

This paper introduces Temporal Density Parallel Coordinates (TDPC) and Depth Cue Parallel Coordinates (DCPC) which extend the standard 2D parallel coordinates technique to capture time-varying dynamics. The proposed techniques can be used to analyse temporal positions of data items as well as temporal positions of changes occurring using 2D displays. To represent temporal changes, polygons (instead of traditional lines) are rendered in parallel coordinates. The results presented show that rendering polygons is superior at revealing large temporal changes. Both TDPC and DCPC have been efficiently implemented on the GPU allowing the visualization of thousands of data items over thousands of time steps at interactive frame rates.
Design of Multi-dimensional Transfer Functions Using Dimensional Reduction
Authors: Francisco de Moura Pinto, Carla M. D. S. Freitas
Published at EuroVis, 2007

Direct volume rendering techniques allow visualization of volume data without extracting intermediate geometry. The mapping from voxel attributes to optical properties is performed by transfer functions which, consequently, play a crucial role in building informative images from the data. One-dimensional transfer functions, which are based only on a scalar value per voxel, often do not provide proper visualizations. On the other hand, multidimensional transfer functions can perform more sophisticated data classification, based on vectorial voxel signatures. The transfer function design is a non-trivial and unintuitive task, especially in the multi-dimensional case. In this paper we propose a multi-dimensional transfer function design technique that uses self-organizing maps to perform dimensional reduction. Our approach gives uniform treatment to volume data containing voxel signatures of arbitrary dimension, and allows the use of any type of voxel attribute as part of the voxel signatures.
Dimensional Congruence for Interactive Visual Data Mining and Knowledge Discovery
Authors: Sebastian Baumgärtner, Achim Ebert, Matthias Deller
Published at EuroVis, 2007

Many authors in the field of 3D human computer interaction have described the advantages of 3D user interfaces: Intuitive metaphors from daily life, immersive workspaces, virtual environments that closely resemble natural environments, and the usefulness of the third dimension as an additional visualization scale. Nevertheless, there are still few or no successful applications for complex information spaces that make use of it in a natural human-centered manner. In this paper, we propose a novel hybrid user interface for knowledge workers to support document spaces and corresponding visualizations. We propose a combined 2D + 3D interface to support both visualization approaches and interaction metaphors to their maximum potential. Interaction is matched due to the principle of dimensional congruence and a thorough investigation of previous approaches and problems is given. Finally, a user study to evaluate the effectiveness and usability of the proposed system is presented.
Feature Emphasis and Contextual Cutaways for Multimodal Medical Visualization
Authors: Michael Burns, Martin Haidacher, Wolfgang Wein, Ivan Viola, M. Eduard Gröller
Published at EuroVis, 2007

Dense clinical data like 3D Computed Tomography (CT) scans can be visualized together with real-time imaging for a number of medical intervention applications. However, it is difficult to provide a fused visualization that allows sufficient spatial perception of the anatomy of interest, as derived from the rich pre-operative scan, while not occluding the real-time image displayed embedded within the volume.

We propose an importance-driven approach that presents the embedded data such that it is clearly visible along with its spatial relation to the surrounding volumetric material. To support this, we present and integrate novel techniques for importance specification, feature emphasis, and contextual cutaway generation. We show results in a clinical context where a pre-operative CT scan is visualized alongside a tracked ultrasound image, such that the important vasculature is depicted between the viewpoint and the ultrasound image, while a more opaque representation of the anatomy is exposed in the surrounding area.
Feature Identification and Extraction in Function Fields
Authors: John C. Anderson, Luke J. Gosink, Mark A. Duchaineau, Kenneth I. Joy
Published at EuroVis, 2007

We present interactive techniques for identifying and extracting features in function fields. Function fields map points in n-dimensional Euclidean space to 1-dimensional scalar functions. Visual feature identification is ac- complished by interactively rendering scalar distance fields, constructed by applying a function-space distance metric over the function field. Combining visual exploration with feature extraction queries, formulated as a set of function-space constraints, facilitates quantitative analysis and annotation. Numerous application domains give rise to function fields. We present results for two-dimensional hyperspectral images, and a simulated time-varying, three-dimensional air quality dataset.
Flexible And Topologically Localized Segmentation
Authors: Gunnar Johansson, Ken Museth, Hamish A. Carr
Published at EuroVis, 2007

One of the most common visualization tasks is the extraction of significant boundaries, often performed with isosurfaces or level set segmentation. Isosurface extraction is simple and can be guided by geometric and topological analysis, yet frequently does not extract the desired boundary. Level set segmentation is better at boundary extraction, but either leads to global segmentation without edges, [CV01], that scales unfavorably in 3D or requires an initial estimate of the boundary from which to locally solve segmentation with edges. We propose a hybrid system in which topological analysis is used for semi-automatic initialization of a level set segmentation, and geometric information bounded topologically is used to guide and accelerate an iterative segmentation algorithm that combines several state-of-the-art level set terms. We thus combine and improve both the flexible isosurface interface and level set segmentation without edges.
Functional Unit Maps for Data-Driven Visualization of High-Density EEG Coherence
Authors: Michael ten Caat, Natasha M. Maurits, Jos B. T. M. Roerdink
Published at EuroVis, 2007

Synchronous electrical activity in different brain regions is generally assumed to imply functional relationships between these regions. A measure for this synchrony is electroencephalography (EEG) coherence, computed between pairs of signals as a function of frequency. Existing high-density EEG coherence visualizations are generally either hypothesis-driven, or data-driven graph visualizations which are cluttered. In this paper, a new method is presented for data-driven visualization of high-density EEG coherence, which strongly reduces clutter and is referred to as functional unit (FU) map. Starting from an initial graph, with vertices representing electrodes and edges representing significant coherences between electrode signals, we define an FU as a set of electrodes represented by a clique consisting of spatially connected vertices. In an FU map, the spatial relationship between electrodes is preserved, and all electrodes in one FU are assigned an identical gray value. Adjacent FUs are visualized with different gray values and FUs are connected by a line if the average coherence between FUs exceeds a threshold. Results obtained with our visualization are in accordance with known electrophysiological findings. FU maps can be used as a preprocessing step for conventional analysis.
Grouse: Feature-Based, Steerable Graph Hierarchy Exploration
Authors: Daniel Archambault, Tamara Munzner, David Auber
Published at EuroVis, 2007

Grouse is a feature-based approach to steerable exploration of a graph and an associated hierarchy. Steerability allows exploration to begin immediately, rather than requiring a costly layout of the entire graph as an initial step. In a feature-based approach, the subgraph inside a metanode of the graph hierarchy is laid out with a well- chosen algorithm appropriate for its topological structure. Grouse preserves the input hierarchy, which provides meaningful information to the user when its metanodes correspond to features of interest. When a metanode in the hierarchy is opened, a limited number of metanodes are laid out again along the path between the opened node and the root. We demonstrate the effectiveness of Grouse on datasets from IMDB, the Internet Movie Database, where nodes are actors and cliques represent movies. The combination of feature-based layout and limited relayout computation does not fragment features in the hierarchy and improves the number of levels in the hierarchy that can be seen at once over previous approaches.
Hardware-accelerated Stippling of Surfaces derived from Medical Volume Data
Authors: Alexandra Baer, Christian Tietjen, Ragnar Bade, Bernhard Preim
Published at EuroVis, 2007

We present a fast hardware-accelerated stippling method which does not require any preprocessing for placing points on surfaces. The surfaces are automatically parameterized in order to apply stippling textures without major distortions. The mapping process is guided by a decomposition of the space in cubes. Seamless scaling with a constant density of points is realized by subdividing and summarizing cubes. Our mip-map technique enables arbitrarily scaling with one texture. Different shading tones and scales are facilitated by adhering to the constraints of tonal art maps. With our stippling technique, it is feasible to encode all scaling and brightness levels within one self-similar texture. Our method is applied to surfaces extracted from (segmented) medical volume data. The speed of the stippling process enables stippling for several complex objects simultaneously. We consider application scenarios in intervention planning (neck and liver surgery planning). In these scenarios, object recognition (shape perception) is supported by adding stippling to semi-transparently shaded objects which are displayed as context information.
Integrating Local Feature Detectors in the Interactive Visual Analysis of Flow Simulation Data
Authors: Raphael Buerger, Philipp Muigg, Martin Ilcík, Helmut Doleisch, Helwig Hauser
Published at EuroVis, 2007

We present smooth formulations of common vortex detectors that allow a seamless integration into the concept of interactive visual analysis of flow simulation data. We express the originally binary feature detectors as fuzzy-sets that can be combined using the linking and brushing concepts of interactive visual analysis. Both interaction and visualization gain from having multiple detectors concurrently available and from the ability to combine them. An application study on automotive data reveals how these vortex detectors combine and perform in praxis.
Interactive Visual Exploration of Unsteady 3D Flows
Authors: Kai Bürger, Jens Schneider 0002, Polina Kondratieva, Jens H. Krüger, Rüdiger Westermann
Published at EuroVis, 2007

In this paper we present GPU-based techniques for the interactive visualization of large unsteady 3D flow fields on uniform grids. We propose a novel dual-core approach to asynchronously stream such fields from the CPU, thus enabling the efficient exploration of large time-resolved sequences. This approach decouples visualization from data handling, resulting in interactive frame rates. Built upon a previously published GPU particle engine for flow visualization we have developed new strategies to compute and to visualize path lines and streak lines on the GPU. To provide additional visual cues, focus+context techniques for polygonal meshes have been integrated. The proposed techniques are used in the visual analysis of the Terashake 2.1 earthquake simulation data, and they have been shown to be very effective in revealing the relevant information in this data.
Interactive Visualization of Multi-Field Medical Data Using Linked Physical and Feature-Space Views
Authors: Jorik Blaas, Charl P. Botha, Frits H. Post
Published at EuroVis, 2007

Multi-field datasets contain multiple parameters defined over the same spatio-temporal domain. In medicine, such multi-field data is being used more often every day, and there is an urgent need for exploratory visualization approaches that are able to deal effectively with the data-analysis. In this paper, we present a highly interactive, coordinated view-based visualization approach that has been developed especially for dealing with multi-field medical data. It can show any number of views of the physical domain and also of the abstract high-dimensional feature space. The approach has been optimized for interactive use with very large datasets. It is based on intuitive interaction techniques, and integrates analysis techniques from pattern classification to guide the exploration process. We will give some details about the implementation, and we demonstrate the utility of our approach with two real medical use cases.
KeyStrokes: Personalizing Typed Text with Visualization
Authors: Petra Neumann 0001, Annie Tat, Torre Zuk, Sheelagh Carpendale
Published at EuroVis, 2007

With the ubiquity of typed text, the style and much of the personality of handwriting has been lost from general communication. To counter this we introduce an artistic real-time visualization of typed messages that additionally captures and encodes aspects of an individual's unique typing style. The potential of our system to augment electronic communication was evaluated and the results are provided along with analysis of their implications for social visualization.
Manual Clustering Refinement using Interaction with Blobs
Authors: Christian Heine 0002, Gerik Scheuermann
Published at EuroVis, 2007

The huge amount of different automatic clustering methods emphasizes one thing: there is no optimal clustering method for all possible cases. In certain application domains, like genomics and natural language processing, it is not even clear if any of the already known clustering methods suffice. In such cases, an automatic clustering method is often followed by manual refinement. The refined version may then be used as either an illustration, a reference, or even an input for a rule based or other machine learning algorithm as a new clustering method. In this paper, we describe a novel interaction technique to manual cluster refinement using the metaphor of soap bubbles, represented by special implicit surfaces (blobs). For instance, entities can simply be moved inside and outside of these blobs. A modified force-directed layout process automatically arranges entities equidistant on the screen. The modifications include a reduction to the expected amount of computation per iteration down to O(|V| log |V|+|E|) in order to achieve a high response time for use in an interactive system. We also spend a considerable amount of effort making the display of blobs fast enough for an interactive system.
Model-free Surface Visualization of Vascular Trees
Authors: Christian Schumann, Steffen Oeltze, Ragnar Bade, Bernhard Preim, Heinz-Otto Peitgen
Published at EuroVis, 2007

Expressive and efficient visualizations of complex vascular structures are essential for medical applications, such as diagnosis and therapy planning. A variety of techniques has been developed which provide smooth high-quality visualizations of vascular structures based on rather simple model assumptions. For diagnostic applications, these model assumptions and the resulting deviations from the actual vessel surface are not acceptable. We present a model-free approach which employs the binary result of a prior vessel segmentation as input. Instead of directly converting the segmentation result into a surface, we compute a point cloud which is adaptively refined at thin structures, where aliasing effects are particularly obvious and artifacts may occur. The point cloud is transformed into a surface representation by means of MPU Implicits, which provide a smooth piecewise quadratic approximation. Our method has been applied to a variety of datasets including pathologic cases. The generated visualizations are considerably more accurate than model-based approaches. Compared to other model-free approaches, our method produces smoother results.