DevLan/vispubs huggingface dataset:
Tuner: Principled Parameter finding for Image Segmentation Algorithms Using Visual Response Surface Exploration
Authors: Thomas Torsney-Weir, Ahmed Saad, Torsten Möller, Hans-Christian Hege, Britta Weber, Jean-Marc Verbavatz, Steven Bergner
Published at Vis, 2011

In this paper we address the difficult problem of parameter-finding in image segmentation. We replace a tedious manual process that is often based on guess-work and luck by a principled approach that systematically explores the parameter space. Our core idea is the following two-stage technique: We start with a sparse sampling of the parameter space and apply a statistical model to estimate the response of the segmentation algorithm. The statistical model incorporates a model of uncertainty of the estimation which we use in conjunction with the actual estimate in (visually) guiding the user towards areas that need refinement by placing additional sample points. In the second stage the user navigates through the parameter space in order to determine areas where the response value (goodness of segmentation) is high. In our exploration we rely on existing ground-truth images in order to evaluate the "goodness" of an image segmentation technique. We evaluate its usefulness by demonstrating this technique on two image segmentation algorithms: a three parameter model to detect microtubules in electron tomograms and an eight parameter model to identify functional regions in dynamic Positron Emission Tomography scans.
Two-Dimensional Time-Dependent Vortex Regions Based on the Acceleration Magnitude
Authors: Jens Kasten, Jan Reininghaus, Ingrid Hotz, Hans-Christian Hege
Published at Vis, 2011

Acceleration is a fundamental quantity of flow fields that captures Galilean invariant properties of particle motion. Considering the magnitude of this field, minima represent characteristic structures of the flow that can be classified as saddle- or vortex-like. We made the interesting observation that vortex-like minima are enclosed by particularly pronounced ridges. This makes it possible to define boundaries of vortex regions in a parameter-free way. Utilizing scalar field topology, a robust algorithm can be designed to extract such boundaries. They can be arbitrarily shaped. An efficient tracking algorithm allows us to display the temporal evolution of vortices. Various vortex models are used to evaluate the method. We apply our method to two-dimensional model systems from computational fluid dynamics and compare the results to those arising from existing definitions.
Visualization of AMR Data With Multi-Level Dual-Mesh Interpolation
Authors: Patrick J. Moran, David Ellsworth
Published at Vis, 2011

We present a new technique for providing interpolation within cell-centered Adaptive Mesh Refinement (AMR) data that achieves C&lt;sup&gt;0&lt;/sup&gt; continuity throughout the 3D domain. Our technique improves on earlier work in that it does not require that adjacent patches differ by at most one refinement level. Our approach takes the dual of each mesh patch and generates "stitching cells" on the fly to fill the gaps between dual meshes. We demonstrate applications of our technique with data from Enzo, an AMR cosmological structure formation simulation code. We show ray-cast visualizations that include contributions from particle data (dark matter and stars, also output by Enzo) and gridded hydrodynamic data. We also show results from isosurface studies, including surfaces in regions where adjacent patches differ by more than one refinement level.
Visualization of Topological Structures in Area-Preserving Maps
Authors: Xavier Tricoche, Christoph Garth, Allen R. Sanderson
Published at Vis, 2011

Area-preserving maps are found across a wide range of scientific and engineering problems. Their study is made challenging by the significant computational effort typically required for their inspection but more fundamentally by the fractal complexity of salient structures. The visual inspection of these maps reveals a remarkable topological picture consisting of fixed (or periodic) points embedded in so-called island chains, invariant manifolds, and regions of ergodic behavior. This paper is concerned with the effective visualization and precise topological analysis of area-preserving maps with two degrees of freedom from numerical or analytical data. Specifically, a method is presented for the automatic extraction and characterization of fixed points and the computation of their invariant manifolds, also known as separatrices, to yield a complete picture of the structures present within the scale and complexity bounds selected by the user. This general approach offers a significant improvement over the visual representations that are so far available for area-preserving maps. The technique is demonstrated on a numerical simulation of magnetic confinement in a fusion reactor.
Volume Analysis Using Multimodal Surface Similarity
Authors: Martin Haidacher, Stefan Bruckner, M. Eduard Gröller
Published at Vis, 2011

The combination of volume data acquired by multiple modalities has been recognized as an important but challenging task. Modalities often differ in the structures they can delineate and their joint information can be used to extend the classification space. However, they frequently exhibit differing types of artifacts which makes the process of exploiting the additional information non-trivial. In this paper, we present a framework based on an information-theoretic measure of isosurface similarity between different modalities to overcome these problems. The resulting similarity space provides a concise overview of the differences between the two modalities, and also serves as the basis for an improved selection of features. Multimodal classification is expressed in terms of similarities and dissimilarities between the isosurfaces of individual modalities, instead of data value combinations. We demonstrate that our approach can be used to robustly extract features in applications such as dual energy computed tomography of parts in industrial manufacturing.
Voronoi-Based Extraction and Visualization of Molecular Paths
Authors: Norbert Lindow, Daniel Baum, Hans-Christian Hege
Published at Vis, 2011

Visual analysis is widely used to study the behavior of molecules. Of particular interest are the analysis of molecular interactions and the investigation of binding sites. For large molecules, however, it is difficult to detect possible binding sites and paths leading to these sites by pure visual inspection. In this paper, we present new methods for the computation and visualization of potential molecular paths. Using a novel filtering method, we extract the significant paths from the Voronoi diagram of spheres. For the interactive visualization of molecules and their paths, we present several methods using deferred shading and other state-of-theart techniques. To allow for a fast overview of reachable regions of the molecule, we illuminate the molecular surface using a large number of light sources placed on the extracted paths. We also provide a method to compute the extension surface of selected paths and visualize it using the skin surface. Furthermore, we use the extension surface to clip the molecule to allow easy visual tracking of even deeply buried paths. The methods are applied to several proteins to demonstrate their usefulness.
Vortex Visualization in Ultra Low Reynolds Number Insect Flight
Authors: Christopher Koehler, Thomas Wischgoll, Haibo Dong, Zachary Gaston
Published at Vis, 2011

We present the visual analysis of a biologically inspired CFD simulation of the deformable flapping wings of a dragonfly as it takes off and begins to maneuver, using vortex detection and integration-based flow lines. The additional seed placement and perceptual challenges introduced by having multiple dynamically deforming objects in the highly unsteady 3D flow domain are addressed. A brief overview of the high speed photogrammetry setup used to capture the dragonfly takeoff, parametric surfaces used for wing reconstruction, CFD solver and underlying flapping flight theory is presented to clarify the importance of several unsteady flight mechanisms, such as the leading edge vortex, that are captured visually. A novel interactive seed placement method is used to simplify the generation of seed curves that stay in the vicinity of relevant flow phenomena as they move with the flapping wings. This method allows a user to define and evaluate the quality of a seed's trajectory over time while working with a single time step. The seed curves are then used to place particles, streamlines and generalized streak lines. The novel concept of flowing seeds is also introduced in order to add visual context about the instantaneous vector fields surrounding smoothly animate streak lines. Tests show this method to be particularly effective at visually capturing vortices that move quickly or that exist for a very brief period of time. In addition, an automatic camera animation method is used to address occlusion issues caused when animating the immersed wing boundaries alongside many geometric flow lines. Each visualization method is presented at multiple time steps during the up-stroke and down-stroke to highlight the formation, attachment and shedding of the leading edge vortices in pairs of wings. Also, the visualizations show evidence of wake capture at stroke reversal which suggests the existence of previously unknown unsteady lift generation mechanisms that are unique to quad wing insects.
WYSIWYG (What You See is What You Get) Volume Visualization
Authors: Hanqi Guo 0001, Ningyu Mao, Xiaoru Yuan
Published at Vis, 2011

In this paper, we propose a volume visualization system that accepts direct manipulation through a sketch-based What You See Is What You Get (WYSIWYG) approach. Similar to the operations in painting applications for 2D images, in our system, a full set of tools have been developed to enable direct volume rendering manipulation of color, transparency, contrast, brightness, and other optical properties by brushing a few strokes on top of the rendered volume image. To be able to smartly identify the targeted features of the volume, our system matches the sparse sketching input with the clustered features both in image space and volume space. To achieve interactivity, both special algorithms to accelerate the input identification and feature matching have been developed and implemented in our system. Without resorting to tuning transfer function parameters, our proposed system accepts sparse stroke inputs and provides users with intuitive, flexible and effective interaction during volume data exploration and visualization.
3D Visualization of temporal changes in bloggers' activities and interests
Authors: Masahiko Itoh, Naoki Yoshinaga 0001, Masashi Toyoda, Masaru Kitsuregawa
Published at VAST, 2011

This paper presents a novel system for analyzing temporal changes in bloggers' activities and interests on a topic through a 3D visualization of dependency structures related to the topic. Having a dependency database built from a blog archive, our 3D visualization framework helps users to interactively exploring temporal changes in bloggers' activities and interests related to the topic.
A state transition approach to understanding users' interactions
Authors: Dong Hyun Jeong, Soo-Yeon Ji, William Ribarsky, Remco Chang
Published at VAST, 2011

Understanding users' interactions is considered as one of the important research topics in visual analytics. Although numerous empirical user studies have been performed to understand a user's interaction, a limited study has been successful in connecting the user's interaction to his/her reasoning. In this paper, we present an approach of understanding experts' interactive analysis by connecting their interactions to conclusions (i.e. findings) through a state transition approach.
A two-stage framework for designing visual analytics system in organizational environments
Authors: Derek Xiaoyu Wang, Wenwen Dou, Thomas Butkiewicz, Eric A. Bier, William Ribarsky
Published at VAST, 2011

A perennially interesting research topic in the field of visual analytics is how to effectively develop systems that support organizational users' decision-making and reasoning processes. The problem is, however, most domain analytical practices generally vary from organization to organization. This leads to diverse designs of visual analytics systems in incorporating domain analytical processes, making it difficult to generalize the success from one domain to another. Exacerbating this problem is the dearth of general models of analytical workflows available to enable such timely and effective designs. To alleviate these problems, we present a two-stage framework for informing the design of a visual analytics system. This design framework builds upon and extends current practices pertaining to analytical workflow and focuses, in particular, on incorporating both general domain analysis processes as well as individual's analytical activities. We illustrate both stages and their design components through examples, and hope this framework will be useful for designing future visual analytics systems. We validate the soundness of our framework with two visual analytics systems, namely Entity Workspace [8] and PatViz [37].
A visual analytics process for maritime resource allocation and risk assessment
Authors: Abish Malik, Ross Maciejewski, Ben Maule, David S. Ebert
Published at VAST, 2011

In this paper, we present our collaborative work with the U.S. Coast Guard's Ninth District and Atlantic Area Commands where we developed a visual analytics system to analyze historic response operations and assess the potential risks in the maritime environment associated with the hypothetical allocation of Coast Guard resources. The system includes linked views and interactive displays that enable the analysis of trends, patterns and anomalies among the U.S. Coast Guard search and rescue (SAR) operations and their associated sorties. Our system allows users to determine the potential change in risks associated with closing certain stations in terms of response time, potential lives and property lost and provides optimal direction as to the nearest available station. We provide maritime risk assessment tools that allow analysts to explore Coast Guard coverage for SAR operations and identify regions of high risk. The system also enables a thorough assessment of all SAR operations conducted by each Coast Guard station in the Great Lakes region. Our system demonstrates the effectiveness of visual analytics in analyzing risk within the maritime domain and is currently being used by analysts at the Coast Guard Atlantic Area.
A visual navigation system for querying neural stem cell imaging data
Authors: Ishwar Kulkarni, Shanaz Y. Mistry, Brian Cummings, Meenakshisundaram Gopi
Published at VAST, 2011

Cellular biology deals with studying the behavior of cells. Current time-lapse imaging microscopes help us capture the progress of experiments at intervals that allow for understanding of the dynamic and kinematic behavior of the cells. On the other hand, these devices generate such massive amounts of data (250GB of data per experiment) that manual sieving of data to identify interesting patterns becomes virtually impossible. In this paper we propose an end-to-end system to analyze time-lapse images of the cultures of human neural stem cells (hNSC), that includes an image processing system to analyze the images to extract all the relevant geometric and statistical features within and between images, a database management system to manage and handle queries on the data, a visual analytic system to navigate through the data, and a visual query system to explore different relationships and correlations between the parameters. In each stage of the pipeline we make novel algorithmic and conceptual contributions, and the entire system design is motivated by many different yet unanswered exploratory questions pursued by our neurobiologist collaborators. With a few examples we show how such abstract biological queries can be analyzed and answered by our system.
An integrated visualization on network events VAST 2011 mini challenge #2 award: "Outstanding integrated overview display"
Authors: Walter Marcelo Lamagna
Published at VAST, 2011

To visualize security trends for the data set provided by the VAST 2011 Mini Challenge #2 a custom tool has been developed. Open source tools [1,2], web programming languages [4,7] and an open source database [3] has been used to work with the data and create a visualization for security log files containing network security trends. In this paper, the tools and methods used for the analysis are described. The methods include the log synchronization with different timezone and the development of heat maps and parallel coordinates charts. To develop the visualization, Processing and Canvas [4,7] was used.
Analysis of large digital collections with interactive visualization
Authors: Weijia Xu, Maria Esteva, Suyog Dott Jain, Varun Jain
Published at VAST, 2011

To make decisions about the long-term preservation and access of large digital collections, archivists gather information such as the collections' contents, their organizational structure, and their file format composition. To date, the process of analyzing a collection - from data gathering to exploratory analysis and final conclusions - has largely been conducted using pen and paper methods. To help archivists analyze large-scale digital collections for archival purposes, we developed an interactive visual analytics application. The application narrows down different kinds of information about the collection, and presents them as meaningful data views. Multiple views and analysis features can be linked or unlinked on demand to enable researchers to compare and contrast different analyses, and to identify trends. We describe and present two user scenarios to show how the application allowed archivists to learn about a collection with accuracy, facilitated decision-making, and helped them arrive at conclusions.
Analyst's workspace: Protecting vastopolis
Authors: Christopher Andrews, Mahmud Shahriar Hossain, Samah Gad, Naren Ramakrishnan, Chris North 0001
Published at VAST, 2011

Analyst's Workspace is a sensemaking environment designed specifically for use of large, high-resolution displays. It employs a spatial workspace to integrate foraging and synthesis activities into a unified process. In this paper we describe how Analyst's Workspace solved the VAST 2011 mini-challenge #3 and discuss some of the unique features of the environment.
Analysts aren't machines: Inferring frustration through visualization interaction
Authors: Lane Harrison, Wenwen Dou, Aidong Lu, William Ribarsky, Derek Xiaoyu Wang
Published at VAST, 2011

Recent work in visual analytics has explored the extent to which information regarding analyst action and reasoning can be inferred from interaction. However, these methods typically rely on humans instead of automatic extraction techniques. Furthermore, there is little discussion regarding the role of user frustration when interacting with a visual interface. We demonstrate that automatic extraction of user frustration is possible given action-level visualization interaction logs. An experiment is described which collects data that accurately reflects user emotion transitions and corresponding interaction sequences. This data is then used in building HiddenMarkov Models (HMMs) which statistically connect interaction events with frustration. The capabilities of HMMs in predicting user frustration are tested using standard machine learning evaluation methods. The resulting classifier serves as a suitable predictor of user frustration that performs similarly across different users and datasets.
Automated measures for interpretable dimensionality reduction for visual classification: A user study
Authors: Ilknur Icke, Andrew Rosenberg
Published at VAST, 2011

This paper studies the interpretability of transformations of labeled higher dimensional data into a 2D representation (scatterplots) for visual classification.&lt;sup&gt;1&lt;/sup&gt;In this context, the term interpretability has two components: the interpretability of the visualization (the image itself) and the interpretability of the visualization axes (the data transformation functions). We define a data transformation function as any linear or non-linear function of the original variables mapping the data into 1D. Even for a small dataset, the space of possible data transformations is beyond the limit of manual exploration, therefore it is important to develop automated techniques that capture both aspects of interpretability so that they can be used to guide the search process without human intervention. The goal of the search process is to find a smaller number of interpretable data transformations for the users to explore. We briefly discuss how we used such automated measures in an evolutionary computing based data dimensionality reduction application for visual analytics. In this paper, we present a two-part user study in which we separately investigated how humans rated the visualizations of labeled data and comprehensibility of mathematical expressions that could be used as data transformation functions. In the first part, we compared human perception with a number of automated measures from the machine learning and visual analytics literature. In the second part, we studied how various structural properties of an expression related to its interpretability.
BaobabView: Interactive construction and analysis of decision trees
Authors: Stef van den Elzen, Jarke J. van Wijk
Published at VAST, 2011

We present a system for the interactive construction and analysis of decision trees that enables domain experts to bring in domain specific knowledge. We identify different user tasks and corresponding requirements, and develop a system incorporating a tight integration of visualization, interaction and algorithmic support. Domain experts are supported in growing, pruning, optimizing and analysing decision trees. Furthermore, we present a scalable decision tree visualization optimized for exploration. We show the effectiveness of our approach by applying the methods to two use cases. The first case illustrates the advantages of interactive construction, the second case demonstrates the effectiveness of analysis of decision trees and exploration of the structure of the data.
Characterizing the intelligence analysis process: Informing visual analytics design through a longitudinal field study
Authors: Youn ah Kang, John T. Stasko
Published at VAST, 2011

While intelligence analysis has been a primary target domain for visual analytics system development, relatively little user and task analysis has been conducted within this area. Our research community's understanding of the work processes and practices of intelligence analysts is not deep enough to adequately address their needs. Without a better understanding of the analysts and their problems, we cannot build visual analytics systems that integrate well with their work processes and truly provide benefit to them. In order to close this knowledge gap, we conducted a longitudinal, observational field study of intelligence analysts in training within the intelligence program at Mercyhurst College. We observed three teams of analysts, each working on an intelligence problem for a ten-week period. Based upon study findings, we describe and characterize processes and methods of intelligence analysis that we observed, make clarifications regarding the processes and practices, and suggest design implications for visual analytics systems for intelligence analysis.