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Live-cell imaging is a common data acquisition technique used by biologists to analyze cell behavior. Since manually tracking cells in a video sequence is extremely time-consuming, many automatic algorithms have been developed in the last twenty years to accomplish the task. However, none of these algorithms can yet claim robust tracking performance at the varying of acquisition conditions (e.g., cell type, acquisition device, cell treatments). While many visualization tools exist to help with cell behavior analysis, there are no tools to help with the algorithm's validation. This paper proposes CellTrackVis, a new visualization tool for evaluating cell tracking algorithms. CellTrackVis allows comparing automatically generated cell tracks with ground truth data to help biologists select the best-suited algorithm for their experimental pipeline. Moreover, CellTackVis can be used as a debugging tool while developing a new cell tracking algorithm to investigate where, when, and why each tracking error occurred., Applications, Weimin Li, Xiang Zhang, Alan Stern, Marc Birtwistle, and Federico Iuricich

We study the problem of computing a spatial scatterplot on a large dataset for arbitrary zooming/panning queries. We introduce a general framework called ''Rainbow'' that generates a high-quality scatterplot for a given result-size budget. Rainbow augments a spatial index with judiciously selected representative points offline. To answer a query, Rainbow traverses the index top-down and selects representative points with a good quality until the result-size budget is reached. We experimentally demonstrate the effectiveness of Rainbow., Rendering and Simulation, Qiushi Bai, Sadeem Alsudais, Chen Li, and Shuang Zhao

We present Blocks, a formalism that enables the building of visualizations by specifying layout, data relationships, and level of detail (LOD) for specific portions of the visualization. Users can create and manipulate Blocks on a canvas interface through drag-and-drop interaction, controlling the LOD of the data attributes for tabular style visualizations. We conducted a user study to compare how 24 participants employ Blocks and Tableau to complete a target visualization task. Findings from the study suggest that Blocks is a useful mechanism for creating visualizations with embedded microcharts, conditional formatting, and custom layouts. We describe future directions for extending Blocks in visual analysis interfaces., Visual Analysis and Machine Learning, Allison Whilden, Dirk Karis, Vidya Setlur, Rodion Degtyar, Jonathan Que, and Filippos Lymperopoulos

We introduce a novel approach for guiding users in the exploration of annotated 2D models using interactive visualization lenses. Information on the interesting areas of the model is encoded in an annotation graph generated at authoring time. Each graph node contains an annotation, in the form of a visual markup of the area of interest, as well as the optimal lens parameters that should be used to explore the annotated area and a scalar representing the annotation importance. Graph edges are used, instead, to represent preferred ordering relations in the presentation of annotations. A scalar associated to each edge determines the strength of this prescription. At run-time, the graph is exploited to assist users in their navigation by determining the next best annotation in the database and moving the lens towards it when the user releases interactive control. The selection is based on the current view and lens parameters, the graph content and structure, and the navigation history. This approach supports the seamless blending of an automatic tour of the data with interactive lens-based exploration. The approach is tested and discussed in the context of the exploration of multi-layer relightable models.

Spatiotemporal measurements such as power consumption, temperature, humidity, movement, noise, brightness, etc., will become ubiquitously available in both old and modern homes to capture and analyze behavioral patterns. The data is fed into analytics platforms and tapped by services but is generally not readily available to consumers for exploration due in part to its inherent complexity and volume. We present an interactive visualization system that uses a simplified 3D representation of building interiors as a canvas for a unified sensor data display. The system's underlying visualization supports spatial as well as temporal accumulation of data, e.g., temperature and humidity values. It introduces a volumetric data interpolation approach which takes 3D room boundaries such as walls, doors, and windows into account. We showcase an interactive, web-based prototype that allows for the exploration of historical as well as real-time data of multiple temperature and humidity sensors. Finally, we sketch an integrated pipeline from sensor data acquisition to visualization, discuss the creation of semantic geometry and subsequent preprocessing, and provide insights into our real-time rendering implementation., EuroVis 2021 - Short Papers, Machine Learning and SciVis Applications, 13, 17, Bastian König, Daniel Limberger, Jan Klimke, Benjamin Hagedorn, and Jürgen Döllner, CCS Concepts: Human-centered computing--> Visualization toolkits; Visualization systems and tools; Information visualization

Engagement in multi-party meetings is a key indicator of outcome. Poor attendee involvement can hinder progress and hurt team cohesion. Thus, there is a strong motivation for organizations to better understand what happens in meetings and improve upon their experience. However, analyzing multi-party meetings is a challenging task, as one needs to consider both verbal exchanges and meeting dynamics among speakers. There is currently a lack of support on these unique tasks. In this paper, we present a new visual approach to help analyze multi-party meetings in industry settings: Discussion Flows, a multi-level interactive visualization tool. Its glyph-based overview allows effortless comparison of overall interactions among different meetings, whereas the individual meeting view uses flow diagrams to convey the relative participation of different speakers throughout the meeting agenda in different levels of details. We demonstrate our approach with meeting recordings from an open source dialogue corpora and use them as the benchmark dataset., EuroVis 2021 - Short Papers, Analytics and Applications, 85, 89, Tao Wang, Mandy Keck, and Zana Vosough, CCS Concepts: Human-centered computing--> Information visualization; Visualization techniques; Interactive systems and tools

In this paper, we present STRONGER, a client-server solution for the online gesture recognition from captured hands' joints sequences. The system leverages a CNN-based recognizer improving current state-of-the-art solutions for segmented gestures classification, trained and tested for the online gesture recognition task on a recent benchmark including heterogeneous gestures. The recognizer provides good classification accuracy and a limited number of false positives on most of the gesture classes of the benchmark used and has been used to create a demo application in a Mixed Reality scenario using an Hololens 2 optical see through Head-Mounted Display with hand tracking capability., Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference, Augmented and Virtual Reality, 109, 117, Marco Emporio, Ariel Caputo, and Andrea Giachetti, CCS Concepts: Computing methodologies --> Neural networks; Human-centered computing --> Gestural input

Hilbert and Moore treemaps are based on the same named space-filling curves to lay out tree-structured data for visualization. One main component of them is a partitioning subroutine, whose algorithmic complexity poses problems when scaling to industry-sized datasets. Further, the subroutine allows for different optimization criteria that result in different layout decisions. This paper proposes conceptual and algorithmic improvements to this partitioning subroutine. Two measures for the quality of partitioning are proposed, resulting in the min-max and min-variance optimization tasks. For both tasks, linear-time algorithms are presented that find an optimal solution. The implementation variants are evaluated with respect to layout metrics and run-time performance against a previously available greedy approach. The results show significantly improved run time and no deterioration in layout metrics, suggesting effective use of Hilbert and Moore treemaps for datasets with millions of nodes., EuroVis 2021 - Short Papers, Information Visualization, 115, 119, Willy Scheibel, Christopher Weyand, Joseph Bethge, and Jürgen Döllner, CCS Concepts: Human-centered computing--> Treemaps; Information visualization

The availability of devices that can record locations and are connected to the Internet creates a huge amount of geospatial data that are continuously streamed. The informative visualization of such data is a challenging problem, given their sheer volume, and the real-time nature of the incoming stream. A simple approach like plotting all datapoints would generate visual noise, and not scale well. To tackle this problem, we have developed a visualization technique based on graceful degradation along three overlaid time periods (ongoing, recent, and history), each with a different visual idiom. A usability test of the proposed technique showed promising results., EuroVis 2021 - Short Papers, Analytics and Applications, 73, 77, João Rafael, João Moreira, Daniel Mendes, Mário Alves, and Daniel Gonçalves, CCS Concepts: Human-centered computing--> Visualization; Visual analytics; Geographic visualization

The timeslice is the predominant method for drawing and visualizing dynamic graphs. However, when nodes and edges have real coordinates along the time axis, it becomes difficult to organize them into discrete timeslices, without a loss of temporal information due to projection. Event-based dynamic graph drawing rejects the notion of a timeslice and allows each node and edge to have its own real-valued time coordinate. Nodes are represented as trajectories of adaptive complexity that are drawn directly in the three-dimensional space-time cube (2D + t). Existing work has demonstrated clear advantages for this approach, but these advantages come at a running time cost. In response to this scalability issue, we present MultiDynNoS, the first multilevel approach for event-based dynamic graph drawing. We consider three operators for coarsening and placement, inspired by Walshaw, GRIP, and FM3, which we couple with an event-based graph drawing algorithm. We evaluate our approach on a selection of real graphs, showing that it outperforms timeslice-based and existing event-based techniques., EuroVis 2021 - Short Papers, Information Visualization, 103, 107, Alessio Arleo, Silvia Miksch, and Daniel Archambault, CCS Concepts: Human-centered computing--> Graph drawings; Visualization

We introduce a novel approach for guiding users in the exploration of annotated 2D models using interactive visualization lenses. Information on the interesting areas of the model is encoded in an annotation graph generated at authoring time. Each graph node contains an annotation, in the form of a visual markup of the area of interest, as well as the optimal lens parameters that should be used to explore the annotated area and a scalar representing the annotation importance. Graph edges are used, instead, to represent preferred ordering relations in the presentation of annotations. A scalar associated to each edge determines the strength of this prescription. At run-time, the graph is exploited to assist users in their navigation by determining the next best annotation in the database and moving the lens towards it when the user releases interactive control. The selection is based on the current view and lens parameters, the graph content and structure, and the navigation history. This approach supports the seamless blending of an automatic tour of the data with interactive lens-based exploration. The approach is tested and discussed in the context of the exploration of multi-layer relightable models., Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference, Short Papers 1: Rendering and Visualization, 85, 90, Moonisa Ahsan, Fabio Marton, Ruggero Pintus, and Enrico Gobbetti, CCS Concepts: Information systems --> Web applications; Human-centered computing --> Graphical user interfaces; Computing methodologies --> Graphics systems and interfaces; Applied computing --> Arts and humanities

This paper describes a ubiquitous computing framework for supporting activities that are strongly associated to a specific physical environment and that are performed by occasional visitors. Our framework implements an activity-centered approach to ubiquitous computing, by defining a conceptual model inspired by Activity Theory and implementing a software infrastructure derived from this conceptual model. The framework has been evaluated from the user view-point by experiments run at different public spaces. We are proposing to perform an additional experiment with the framework, providing user assistance to Interac����o 2006 participants and organizers., Interac����o 2006 - 2�� Confer��ncia Nacional em Interac����o Pessoa-M��quina, Posters e Demos, 221, 224, Helder Pinto and Rui Jos��, Ubiquitous computing frameworks, activity-centered computing

Ensemble methods are widely used to simulate complex non-linear systems and to estimate forecast uncertainty. However, visualizing and analyzing ensemble data is challenging, in particular when multimodality arises, i.e., distinct likely outcomes. We propose a graph-based approach that explores multimodality in univariate ensemble data from weather prediction. Our solution utilizes clustering and a novel concept of life span associated with each cluster. We applied our method to historical predictions of extreme weather events and illustrate that our method aids the understanding of the respective ensemble forecasts., Machine Learning Methods in Visualisation for Big Data, Papers, 7, 11, Natacha Galmiche, Helwig Hauser, Thomas Spengler, Clemens Spensberger, Morten Brun, and Nello Blaser, CCS Concepts: Applied computing --> Earth and atmospheric sciences; Human-centered computing --> Visual analytics; Computing methodologies --> Unsupervised learning

While sailing, sailors rely on their eyes to inspect the sail shape and adjust the configurations to achieve an appropriate shape for a certain the weather condition. Mastering this so-called trimming process requires years of experience since the visual inspection of the sail shape suffers from inaccuracies and many times are difficult to communicate verbally. Therefore, this research proposes a visual analysis tool that presents an accurate sail shape representation and supports sailors in investigating the optimal sail shape for certain weather conditions. In order to achieve our goals, we reconstruct the 3D sail shape from point clouds acquired by photogrammetry methods. For incomplete acquisitions we deform a complete template sail to estimate the missing parts. We designed a visualization dashboard for sailors to explore the 3D structure, 2D profiles and characteristics of the time-varying sail shape as well as analyze their relation to boat speed. The usability of the visualization tool is tested through a qualitative evaluation with two sailing experts. The result shows that the reconstruction and deformation of sail shape are plausible. Furthermore, the visualization dashboard has the potential to enhance sailors' comprehension of sail shape and provide insights towards optimal trimming., EuroVis 2021 - Short Papers, Machine Learning and SciVis Applications, 19, 23, Danfeng Mu, Marcos Pieras, Douwe Broekens, and Ricardo Marroquim, CCS Concepts: Human-centered computing--> Information visualization

Choosing salient time steps from spatio-temporal data is useful for summarizing the sequence and developing visualizations for animations prior to committing time and resources to their production on an entire time series. Animations can be developed more quickly with visualization choices that work best for a small set of the important salient timesteps. Here we introduce a new unsupervised learning method for finding such salient timesteps. The volumetric data is represented by a 4-dimensional non-negative tensor, X(t; x; y; z).The presence of latent (not directly observable) structure in this tensor allows a unique representation and compression of the data. To extract the latent time-features we utilize non-negative Tucker tensor decomposition. We then map these time-features to their maximal values to identify the salient time steps. We demonstrate that this choice of time steps allows a good representation of the time series as a whole., EuroVis 2021 - Short Papers, Scientific Visualization, 55, 59, Jesus Pulido, John Patchett, Manish Bhattarai, Boian Alexandrov, and James Ahrens, CCS Concepts: Human-centered computing--> Visualization design and evaluation methods

Convolutional neural networks (CNNs) are popularly used in a wide range of applications, such as computer vision, natural language processing, and human-computer interaction. However, testing and understanding a trained model is difficult and very time-consuming. This is because their inner mechanisms are often considered as a 'black-box' due to difficulty in understanding the causal relationships between processes and results. To help the testing and understanding of such models, we present a user-interactive visual analytics system, VATUN, to analyze a CNN-based image classification model. Users can accomplish the following four tasks in our integrated system: (1) detect data instances in which the model confuses classification, (2) compare outcomes of the model by manipulating the conditions of the image, (3) understand reasons for the prediction of the model by highlighting highly influential parts from the image, and (4) analyze the overall what-if scenarios when augmenting the instances for each class. Moreover, by combining multiple techniques, our system lets users analyze behavior of the model from various perspectives. We conduct a user study of an image classification scenario with three domain experts. Our study will contribute to reducing the time cost for testing and understanding the CNN-based models in several industrial areas., EuroVis 2021 - Short Papers, Machine Learning and SciVis Applications, 7, 11, Cheonbok Park, Soyoung Yang, Inyoup Na, Sunghyo Chung, Sungbok Shin, Bum Chul Kwon, Deokgun Park, and Jaegul Choo, CCS Concepts: Human-centered computing--> Visualization toolkits

Techniques for presenting objects spatially via density maps have been thoroughly studied, but there is lack of research on how to display this information in the presence of several classes, i.e., multiclass density maps. Moreover, there is even less research on how to design an interactive visualization for comparison tasks on multiclass density maps. One application domain which requires this type of visualization for comparison tasks is crime analytics, and the lack of research in this area results in ineffective visual designs. To fill this gap, we study four types of techniques to compare multiclass density maps, using car theft data. The interactive techniques studied are swipe, translucent overlay, magic lens, and juxtaposition. The results of a user study (N=32) indicate that juxtaposition yields the worst performance to compare distributions, whereas swipe and magic lens perform the best in terms of time needed to complete the experiment. Our research provides empirical evidence on how to design interactive idioms for multiclass density spatial data, and it opens a line of research for other domains and visual tasks., EuroVis 2021 - Short Papers, Analytics and Applications, 79, 83, Lukas Svicarovic, Denis Parra, and María Jesús Lobo, CCS Concepts: Human-centered computing--> Empirical studies in visualization; Visual analytics

General visualization recommendation systems typically make design decisions of the dataset automatically. However, these systems are only able to prune meaningless visualizations but fail to recommend targeted results. In this paper, we contributed TaskVis, a task-oriented visualization recommendation approach with detailed modeling of the user's analysis task. We first summarized a task base with 18 analysis tasks by a survey both in academia and industry. On this basis, we further maintained a rule base, which extends empirical wisdom with our targeted modeling of analysis tasks. Inspired by Draco, we enumerated candidate visualizations through answer set programming. After visualization generation, TaskVis supports four ranking schemes according to the complexity of charts, coverage of the user's interested columns and tasks. In two user studies, we found that TaskVis can well reflect the user's preferences and strike a great balance between automation and the user's intent., EuroVis 2021 - Short Papers, Information Visualization, 91, 95, Leixian Shen, Enya Shen, Zhiwei Tai, Yiran Song, and Jianmin Wang, CCS Concepts: Human-centered computing--> Information visualization; Information Systems--> Data analytics

Recent advancements in multivariate data visualization have opened new research opportunities for the visualization community. In this paper, we propose an uncertain multivariate data visualization technique called feature confidence level-sets. Conceptually, feature level-sets refer to level-sets of multivariate data. Our proposed technique extends the existing idea of univariate confidence isosurfaces to multivariate feature level-sets. Feature confidence level-sets are computed by considering the trait for a specific feature, a confidence interval, and the distribution of data at each grid point in the domain. Using uncertain multivariate data sets, we demonstrate the utility of the technique to visualize regions with uncertainty in relation to the specific trait or feature, and the ability of the technique to provide secondary feature structure visualization based on uncertainty., EuroVis 2021 - Short Papers, Scientific Visualization, 43, 47, Sudhanshu Sane, Tushar M. Athawale, and Chris R. Johnson, CCS Concepts: Human-centered computing--> Scientific visualization

Oceanic eddies, which are highly mass-coherent vortices traveling through the earth's waters, are of special interest for their mixing properties. Therefore, large-scale ensemble simulations are performed to approximate their possible evolution. Analyzing their development and transport behavior requires a stable extraction of both their shape and properties of water masses within. We present a framework for extracting the time series of full 3D eddy geometries based on an winding angle criterion. Our analysis tools enables users to explore the results in-depth by linking extracted volumes to extensive statistics collected across several ensemble members. The methods are showcased on an ensemble simulation of the Red Sea. We show that our extraction produces stable and coherent geometries even for highly irregular eddies in the Red Sea. These capabilities are utilized to evaluate the stability of our method with respect to variations of user-defined parameters. Feedback gathered from domain experts was very positive and indicates that our methods will be considered for newly simulated, even larger data sets., Workshop on Visualisation in Environmental Sciences (EnvirVis), Probabilistic and Uncertainty-based Techniques for Environmental Data Visualization, 17, 24, Anke Friederici, Martin Falk, and Ingrid Hotz, Categories and Subject Descriptors (according to ACM CCS): [Computer Graphics]: Human-centered computing-Scientific visualization

This paper presents an in situ visualization algorithm for neural network training. As each training data item leads to multiple hidden variables when being forward-propagated through a neural network, our algorithm first estimates how much each hidden variable contributes to the training loss. Based on linear approximation, we can approximate the contribution mainly based on the forward-propagated value and the backward-propagated derivative per hidden variable, both of which are available during the training with no cost. By aggregating the loss contribution of hidden variables per data item, we can detect difficult data items that contribute most to the loss, which can be ambiguous or even incorrectly labeled. For convolution neural networks (CNN) with images as inputs, we extend the estimation of loss contribution to measure how different image areas impact the loss, which can be visualized over time to see how a CNN evolves to handle ambiguous images., EuroVis 2021 - Short Papers, Machine Learning and SciVis Applications, 1, 5, Teng-Yok Lee, CCS Concepts: Human-centered computing--> Scientific visualization

In this work we propose an integration-aware super-resolution approach for 3D vector fields. Recent work in flow field superresolution has achieved remarkable success using deep learning approaches. However, existing approaches fail to account for how vector fields are used in practice, once an upsampled vector field is obtained. Specifically, a cornerstone of flow visualization is the visual analysis of streamlines, or integral curves of the vector field. To this end, we study how to incorporate streamlines as part of super-resolution in a deep learning context, such that upsampled vector fields are optimized to produce streamlines that resemble the ground truth upon integration. We consider common factors of integration as part of our approach - seeding, streamline length - and how these factors impact the resulting upsampled vector field. To demonstrate the effectiveness of our approach, we evaluate our model both quantitatively and qualitatively on different flow field datasets and compare our method against state of the art techniques., EuroVis 2021 - Short Papers, Scientific Visualization, 49, 53, Saroj Sahoo and Matthew Berger, CCS Concepts: Computing methodologies--> Neural networks; Reconstruction; Human-centered computing--> Scientific visualization

En este trabajo se presenta una aplicación desarrollada para enriquecer y ampliar las técnicas actuales de registro arqueológico. Basada en una arquitectura cliente-servidor, se ha utilizado el motor de videojuegos Unity para implementar una aplicación cliente sencilla e intuitiva que permite realizar la reconstrucción virtual de un yacimiento a partir del escaneado 3D in situ del terreno excavado, así como del escaneado 3D en laboratorio de los hallazgos más importantes. Así se consigue preservar la información espacial del yacimiento, y se facilita la visita virtual del mismo desde cualquier equipo conectado a Internet., Spanish Computer Graphics Conference (CEIG), Short Papers, 23, 26, Alberto Calzado-Martínez, Ángel Luis García-Fernández, and Lidia M. Ortega-Alvarado, CCS Concepts: Applied computing --> Arts and humanities; Human-centered computing --> Graphical user interfaces; Information visualization; Computing methodologies --> Virtual reality

Interactive spatial arrangement and grouping (A&G) of images is a critical step of the sense-making process. We argue that to support A&G tasks, a visual encoding idiom should avoid clutter, show groups explicitly, and maximize the use of space while allowing free positioning. None of the existing interactive idioms supporting A&G tasks optimizes all these criteria at once. We propose and implement an interactive Voronoi treemap for A&G that fulfills all these requirements. The cells representing groups or objects can be dragged or clicked to arrange objects and groups and to create, merge, split, expand, or collapse groups. We present a usage scenario for an art quiz game and a comparative analysis of our approach to the recent Piling.js library for a categorization task of HiC data images. We discuss limitations and future work., EuroVis 2021 - Short Papers, Information Visualization, 97, 101, Ala Abuthawabeh and Michael Aupetit, CCS Concepts: Human-centered computing--> Treemaps; Visualization design and evaluation methods

Both geometric and semantic information are required for a complete understanding of regions acquired as three-dimensional (3D) point clouds using the Light Detection and Ranging (LiDAR) technology. However, the global descriptors of such datasets that integrate both the information types are rare. With a focus on airborne LiDAR point clouds, we propose a novel global descriptor that transforms the point cloud from Cartesian to barycentric coordinate spaces. We use both the probabilistic geometric classification, aggregated from multiple scales, and the semantic classification to construct our descriptor using point rendering. Thus, we get an image-based multiscale global descriptor, IMGD. To demonstrate its usability, we propose the use of distribution distance measures between the descriptors for comparing the point clouds. Our experimental results demonstrate the effectiveness of our descriptor, when constructed of publicly available datasets, and on applying our selected distance measures., Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference, Modeling, Reconstruction, and Applications, 61, 72, Jaya Sreevalsan-Nair, Pragyan Mohapatra, and Satendra Singh, Keywords: Airborne LiDAR point clouds, Local geometric descriptors, Global descriptor, Classification, Barycentric coordinates, Visualization, Shannon entropy, Distribution distance measure, Uncertainty analysis, Covariance tensor, Tensor voting CCS Concepts: Computing methodologies --> Image representations; Human-centered computing --> Visualization techniques; Information systems --> Nearest-neighbor search

Analyzing body movement as a means of expression is of interest in diverse areas, such as dance, sports, films, as well as anthropology or archaeology. In particular, in choreography, body movements are at the core of artistic expression. Dance moves are composed of spatial and temporal structures that are difficult to address without interactive visual data analysis tools. We present a visual analytics solution that allows the user to get an overview of, compare, and visually search dance move features in video archives. With the help of similarity measures, a user can compare dance moves and assess dance poses. We illustrate our approach through three use cases and an analysis of the performance of our similarity measures. The expert feedback and the experimental results show that 75% to 80% of dance moves can correctly be categorized. Domain experts recognize great potential in this standardized analysis. Comparative and motion analysis allows them to get detailed insights into temporal and spatial development of motion patterns and poses., EuroVis 2021 - Short Papers, Analytics and Applications, 67, 71, Vasiliki Arpatzoglou, Artemis Kardara, Alexandra Diehl, Barbara Flueckiger, Sven Helmer, and Renato Pajarola, CCS Concepts: Human-centered computing--> Visual analytics

We present an analysis of the impact of hyper-parameters for an ensemble of neural networks using tailored visualization techniques to understand the complicated relationship between hyper-parameters and model performance. The high-dimensional error surface spanned by the wide range of hyper-parameters used to specify and optimize neural networks is difficult to characterize - it is non-convex and discontinuous, and there could be complex local dependencies between hyper-parameters. To explore these dependencies, we make use of a large number of sampled relations between hyper-parameters and end performance, retrieved from thousands of individually trained convolutional neural network classifiers. We use a structured selection of visualization techniques to analyze the impact of different combinations of hyper-parameters. The results reveal how complicated dependencies between hyper-parameters influence the end performance, demonstrating how the complete picture painted by considering a large number of trainings simultaneously can aid in understanding the impact of hyper-parameter combinations., Machine Learning Methods in Visualisation for Big Data, Papers, 13, 17, Daniel Jönsson, Gabriel Eilertsen, Hezi Shi, Jianmin Zheng, Anders Ynnerman, and Jonas Unger, CCS Concepts: Computing methodologies --> Neural networks; Human-centered computing --> Visual analytics

Visualization literacy, the ability to interpret and understand visual designs, has gained momentum in the educational and information visualization communities. The goal of this research is to identify and address barriers to treemap literacy - a popular visual design, with a view to improve a non-expert user's treemap visualization literacy skills. In this paper we present the results of two years of an information visualization assignment, which are used to identify the barriers to and challenges of understanding and creating treemaps. From this, we develop a treemap visualization literacy test. Then, we propose a pedagogical tool that facilitates both teaching and learning of treemaps and advances treemap visualization literacy. To investigate the efficiency of this educational software, we then conduct a classroom-based study with 25 participants. We identify the properties of treemaps that can hinder literacy and cognition based on the results from the treemap visualization literacy test. Results also provide further support for the use of our tool that had a positive effect on treemap literacy skills of university students., Eurographics 2020 - Education Papers, Session 3, 29, 38, Elif E. Firat, Alena Denisova, and Robert S. Laramee, CCS Concepts: Human-centered computing --> Visualization systems and tools; Empirical studies in visualization

Memory leaks occur when no longer needed objects are unnecessarily kept alive. They can have a significant negative performance impact, leading to a crash in the worst case. Thus, tool support for heap evolution analysis, especially memory leak analysis, is essential. Unfortunately, most memory analysis tools lack advanced visualizations to facilitate this task. In this paper, we present an approach to use well-known tree visualization techniques for memory growth visualization. Our approach groups heap objects into memory trees based on a user-defined set of properties such as their types or their allocation sites at multiple points in time. We present two novel approaches to inspect how these trees evolve over time: In our time-travelbased visualization, a single space-filling tree visualization shows the monitored application's heap memory at a given point in time. Users can step back and forth in time, causing the visualization to update itself. In our timeline-based visualization, a time-series chart depicts the overall memory consumption over time. Above this chart, multiple memory tree visualizations are shown side-by-side for a number of user-selected points in time. Using these techniques to visually inspect the evolution of the heap over time should enable users to gain new insights and to detect (problematic) memory trends in their applications. To demonstrate the feasibility and applicability of the presented approach, we integrated it into AntTracks, a trace-based memory monitoring tool and applied it in two memory leak case studies., Smart Tools and Apps for Graphics - Eurographics Italian Chapter Conference, Tools, 63, 75, Markus Weninger, Lukas Makor, and Hanspeter Mössenböck, CCS Concepts: General and reference --> Performance;Software and its engineering --> Software performance; Software maintenance tools;Information systems --> Data analytics; Information extraction;Human-centered computing --> Interactive systems and tools; Visualization techniques; Visual analytics; Information visualization

Explainable artificial intelligence (XAI) methods aim to reveal the non-transparent decision-making mechanisms of black-box models. The evaluation of insight generated by such XAI methods remains challenging as the applied techniques depend on many factors (e.g., parameters and human interpretation). We propose ModelSpeX, a visual analytics workflow to interactively extract human-centered rule-sets to generate model specifications from black-box models (e.g., neural networks). The workflow enables to reason about the underlying problem, to extract decision rule sets, and to evaluate the suitability of the model for a particular task. An exemplary usage scenario walks an analyst trough the steps of the workflow to show the applicability., Machine Learning Methods in Visualisation for Big Data, Papers, 7, 11, Udo Schlegel, Eren Cakmak, and Daniel A. Keim, CCS Concepts: Computing methodologies --> Artificial intelligence; Human-centered computing --> HCI theory, concepts and models

Visual quality metrics describe the quality and efficiency of multidimensional data visualizations in order to guide data analysts during exploration tasks. Current metrics are usually based on empirical algorithms which do not accurately represent human perception and therefore often differ from the analysts' expectations. We propose a new perception-based quality metric using deep learning that rates the correlation of data dimensions visualized by scatterplots. First, we created a data set containing over 15,000 pairs of scatterplots with human annotations on the perceived correlation between the data dimensions. Afterwards, we trained two different Convolutional Neural Networks (CNN), one extracts features from scatterplot images and the other directly from data vectors. We evaluated both CNNs on our test set and compared them to previous visual quality metrics. The experiments show that our new metric is able to represent human perception more accurately than previous methods., Vision, Modeling and Visualization, Machine Learning in Vision and Analysis, 55, 62, Leslie Wöhler, Yuxin Zou, Moritz Mühlhausen, Georgia Albuquerque, and Marcus Magnor, CCS Concepts: General and reference --> Metrics; Human-centered computing --> Visual analytics; Computing methodologies --> Perception; Neural networks

The demand for augmented reality applications is rapidly growing. In many domains, we observe a new interest for this technology, stressing the need for more efficient ways of producing augmented content. Similarly to virtual reality, interactive objects in augmented reality are a powerful means to improve the experience. While it is now well democratized for virtual reality, interactivity is still finding its way into augmented reality. To open the way to this interactive augmented reality, we designed a new methodology for the management of the interactions in augmented reality, supported by an authoring tool for the use by designers and domain experts. This tool makes the production of interactive augmented content faster, while being scalable to the needs of each application. Usually in the creation of applications, a large amount of time is spent through discussions between the designer (or the domain expert), carrying the needs of the application, and the developer, holding the knowledge to create it. Thanks to our tool, we reduce this time by allowing the designer to create an interactive application, without having to write a single line of code., ICAT-EGVE 2019 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments, Design and Programming, 89, 96, Flavien Lécuyer, Valérie Gouranton, Adrien Reuzeau, Ronan Gaugne, and Bruno Arnaldi, CCS Concepts: Human-centered computing --> Mixed / augmented reality; Activity centered design; Interface design prototyping; Interaction design theory, concepts and paradigms

In this article, we present a framework for an immersive and interactive 3D manipulation of large point clouds, in the context of an archaeological study. The framework was designed in an interdisciplinary collaboration with archaeologists.We first applied this framework for the study of an 17th-century building of a Real Tennis court. We propose a display infrastructure associated with a set of tools that allows archaeologists to interact directly with the point cloud within their study process. The resulting framework allows an immersive navigation at scale 1:1 in a dense point cloud, the manipulation and production of cut plans and cross sections, and the positioning and visualisation of photographic views. We also apply the same framework to three other archaeological contexts with different purposes, a 13th century ruined chapel, a 19th-century wreck and a cremation urn from the Iron Age., ICAT-EGVE 2019 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments, Simulation and Visualization, 73, 80, Ronan Gaugne, Quentin Petit, Jean-Baptiste Barreau, and Valérie Gouranton, CCS Concepts: Human-centered computing --> Virtual reality; Applied computing --> Archaeology

In this paper, the two major components of a new multi-layer framework ideal for two-handed interaction in desktop virtual environments called Library for Interactive Settings of User-Mode (LISU) are explained. In addition, we evaluate LISU performance with a group of participants and we report some of our initial results by giving an analysis of user experiences, and interaction speed., Computer Graphics and Visual Computing (CGVC), Posters, 97, 101, Mario Sandoval, Tim Morris, and Martin Turner, CCS Concepts: Human-centered computing --> HCI design and evaluation methods; Virtual reality; Interaction devices; Computing methodologies --> Graphics systems and interfaces; Hardware --> Signal processing systems

We present our vision and steps toward implementing a collaborative 3D data analysis tool based on wearable Augmented Reality Head-Mounted Display (AR-HMD). We envision a hybrid environment which combines such AR-HMD devices with multi-touch devices to allow multiple collaborators to visualize and jointly discuss volumetric datasets. The multi-touch devices permit users to manipulate the datasets' states, either publicly or privately, while also proposing means for 2D input for, e. g., drawing annotations. The headsets allow each user to visualize the dataset in physically correct perspective stereoscopy, either in public or in their private space. The public space is viewed by all, with modifications shared in real-time. The private space allows each user to investigate the same dataset with their own preferences, for instance, with a different clipping range. The user can later decide to merge their private space with the public one or cancel the changes., EuroVis 2019 - Posters, Posters, 21, 23, Mickael Sereno, Lonni Besançon, and Tobias Isenberg, CCS Concepts: Human-centered computing --> Scientific visualization; Interaction techniques; Synchronous editors

The CyberAnthill is both a generative sculpture and a Live Computational Sculpting (LCS) system that uses a 3D printer and custom software to build plastic sculptures out of layered cellular automata. As the title alludes to, the cellular automata are inspired by Langston's Ant and the light cycle racers in the cult 1980's science-fiction movie Tron. Instead of the normal process of printing exacting, predetermined 3D models, the 3D printer generates its plastic forms by running unpredictable computer code., ACM/EG Expressive Symposium - Posters, Demos, and Artworks, Art in Motion, 3, 4, Evan Raskob, CCS Concepts: Human-centered computing --> Visualization systems and tools; Computing methodologies --> Simulation types and techniques; Applied computing --> Fine arts

International audience; We introduce IATK, the Immersive Analytics Toolkit, a software package for Unity that allows interactive authoring and exploration of data visualisation in immersive environments. The design of IATK was informed by interdisciplinary expert-collaborations as well as visual analytics applications and iterative refinement over several years. IATK allows for easy assembly of visualisations through a grammar of graphics that a user can configure in a GUI— in addition to a dedicated visualisation API that supports the creation of novel immersive visualisation designs and interactions. IATK is designed with scalability in mind, allowing visualisation and fluid responsive interactions in the order of several million points at a usable frame rate. This paper outlines our design requirements, IATK’s framework design and technical features, its user interface, as well as application examples.

Sound and light signal propagation have similar physical properties. This provides inspiration for creating an audio-visual echolocation system, where light is mapped to the sound signal, visually representing auralization of the virtual environment (VE). Some mammals navigate using echolocation; however humans are less successful with this. To the authors' knowledge, it remains to be seen if sound propagation and its visualization have been implemented in a perceptually pleasant way and is used for navigation purposes in the VE. Therefore, the core novelty of this research is navigation with visualized echolocation signal using a cognitive mental mapping activity in the VE.

We present an assessment of asymmetric interactions in Collaborative Virtual Environments (CVEs). In our asymmetric setup, two co-located users interact with virtual 3D objects, one in immersive Virtual Reality (VR) and the other in mobile Augmented Reality (AR). We conducted a study with 36 participants to evaluate performance and collaboration aspects of pair work, and compare it with two symmetric scenarios, either with both users in immersive VR or mobile AR. To perform this experiment, we adopt a collaborative AR manipulation technique from literature and develop and evaluate a VR manipulation technique of our own. Our results indicate that pairs in asymmetric VR-AR achieved significantly better performance than the AR symmetric condition, and similar performance to VR symmetric. Regardless of the condition, pairs had similar work participation indicating a high cooperation level even when there is a visualization and interaction asymmetry between the participants.

Immersive analytics allows a large amount of data and complex structures to be concurrently investigated. We propose a collaborative analytics system that benefits from new advances in immersive technologies for collaborators working in the early stages of data exploration. We implemented a combination of Star Coordinates and Star Plot visualisation techniques to support the visualisation of multidimensional data and the encoding of datasets using simple and compact visual representations. To support data analytics tasks, we propose tools and interaction techniques for users to build decision trees for visualising and analysing data in a top-down method Refereed/Peer-reviewed

In cultural heritage collections, categorization is a central technique used to distinguish cultural movements, styles, or genres. For that end, objects are tagged with set-typed metadata and other information, such as time of origin. Visualizations can communicate how such sets organize a collection - and how they change over time. But existing interfaces fall short of a) representing an overview of temporal set-developments in an integrated fashion and b) of representing the set elements (i.e., the cultural objects) themselves to be contemplated on demand. Against this background, we introduce two integrated visualization techniques - a superimposition and a space-time cube view - depicting the development of sets and their elements over time. We share first results from a qualitative evaluation with casual users and outline open challenges for future research., EuroVis 2019 - Posters, Posters, 45, 47, Saminu Salisu, Eva Mayr, Velitchko Andreev Filipov, Roger A. Leite, Silvia Miksch, and Florian Windhager, CCS Concepts: Human-centered computing --> Information visualization; Computing methodologies --> Temporal reasoning; Applied computing --> Arts and humanities

Refereed/Peer-reviewed Freehand gesture interaction has long been proposed as a `natural' input method for Augmented Reality (AR) applications, yet has been little explored for intensive applications like multiscale navigation. In multiscale navigation, such as digital map navigation, pan and zoom are the predominant interactions. A position-based input mapping (e.g. grabbing metaphor) is intuitive for such interactions, but is prone to arm fatigue. This work focuses on improving digital map navigation in AR with mid-air hand gestures, using a horizontal intangible map display. First, we conducted a user study to explore the effects of handedness (unimanual and bimanual) and input mapping (position-based and rate-based). From these findings we designed DiveZoom and TerraceZoom, two novel hybrid techniques that smoothly transition between position- and rate-based mappings. A second user study evaluated these designs. Our results indicate that the introduced input-mapping transitions can reduce perceived arm fatigue with limited impact on performance.

We propose an approach to interactively create exploded views of molecular structures with the goal to help domain experts in their design process and provide them with a meaningful visual representation of component relationships. Exploded views are excellently suited to manage visual occlusion of structure components, which is one of the main challenges when visualizing complex 3D data. In this paper, we discuss four key parameters of an exploded view: explosion distance, direction, order, and the selection of explosion components. We propose two strategies, namely the structure-derived exploded view and the interactive free-form exploded view, for computing these four parameters systematically. The first strategy allows scientists to automatically create exploded views by computing the parameters from the given object structures. The second strategy further supports them to design and customize detailed explosion paths through user interaction. Our approach features the possibility to animate exploded views, to incorporate ease functions into these animations and to display the explosion path of components via arrows. Finally, we demonstrate three use cases with various challenges that we investigated in collaboration with a domain scientist. Our approach, therefore, provides interesting new ways of investigating and presenting the design layout and composition of complex molecular structures.

Sarajevo War Tunnel can not be visited any more. It was closed just after the war due to the airport runway security. A small part (20m) can be seen in the Tunnel Museum. The only way to experience passing through this object, crucial for Sarajevo survival during the war, is Virtual Reality (VR). The paper describes the Sarajevo War Tunnel VR project, a virtual cultural heritage application combining VR storytelling about the Sarajevo siege with the VR simulation of the tunnel crossing. The user experience evaluation shows the potential of VR technologies in presentation of dark heritage., Eurographics Workshop on Graphics and Cultural Heritage, Storytelling in CH, 1, 6, Selma Rizvic, Dusanka Boskovic, Vensada Okanovic, Ivona Ivkovic Kihic, and Sanda Sljivo, CCS Concepts: Human-centered computing --> HCI design and evaluation methods; Computing methodologies --> Virtual reality; Applied computing --> Education

In many application scenarios, outliers can be associated with specific importance for various reasons. In such cases, labeling outliers is important to connect them to the actual semantics of the respective entity. In this paper, we present a cost-based greedy approach that places labels with outliers within scatterplots. The approach uses a search strategy to find the position that represents the least cost to place labels. Our approach can also produce different labeling outcomes by adjusting the weights of the criteria of the cost function. We demonstrate our approach with scatterplots produced from object-oriented software metrics, where outliers often relate to bad smells in the software., EuroVis 2019 - Short Papers, Design and Evaluation, 1, 5, Haris Mumtaz, Mereke van Garderen, Fabian Beck, and Daniel Weiskopf, CCS Concepts: Human-centered computing --> Visualization; Visualization application domains; Information visualization

The objective of this research is to compare the effectiveness of various virtual reality tracking systems underwater. There have been few works in aquatic virtual reality (VR) - i.e., VR systems that can be used in a real underwater environment. Moreover, the works that have been done have noted limitations on tracking accuracy. Our initial test results suggest that inertial measurement units work well underwater for orientation tracking but a different approach is needed for position tracking. Towards this goal, we have waterproofed and evaluated several consumer tracking systems intended for gaming to determine the most effective approaches. First, we informally tested infrared systems and fiducial marker based systems, which demonstrated significant limitations of optical approaches. Next, we quantitatively compared inertial measurement units (IMU) and a magnetic tracking system both above water (as a baseline) and underwater. By comparing the devices' rotation data, we have discovered that the magnetic tracking system implemented by the Razer Hydra is approximately as accurate underwater as compared to a phone-based IMU. This suggests that magnetic tracking systems should be further explored as a possibility for underwater VR applications., ICAT-EGVE 2019 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments, Tracking and Positioning, 33, 36, Raphael Costa, Rongkai Guo, and John Quarles, CCS Concepts: Human-centered computing --> Interaction devices; Hardware --> Hardware reliability screening; Computing methodologies --> Virtual reality

The weather and climate research community needs to analyze increasingly large datasets, mostly obtained by observations or produced by simulations. Ensemble simulation techniques, which are used to capture uncertainty, add a further dimension to the multivariate time-dependent 3D data, even tightening the challenge of finding relevant information in the data for answering the respective research questions. In this paper we propose a topology-based method to support the visual analysis of climate data by detecting regions with particularly strong local minima or maxima and highlighting them with colored contours. Combined with preceding clustering of the data fields, typical spatial patterns characterizing the climate variability are detected and visualized. We demonstrate the utility of our method with a study of global temperature anomalies of a 150-years ensemble simulation consisting of 100 members., Workshop on Visualisation in Environmental Sciences (EnvirVis), Weather and Climate, 9, 16, Christopher P. Kappe, Michael Böttinger, and Heike Leitte, CCS Concepts: Human-centered computing-->Geographic visualization; Applied computing-->Environmental sciences

Monitoring, analyzing and determining the production quality in a complex and long-running process such as in the aluminum production is a challenging task. We aim to support production data exploration in the aluminum industry. To this end, we developed the first version of the interactive visual analytics tool ADAM. The main aspect of concern is product quality, which is obtained from the quality inspection of aluminum plates at the end of the production process. A set of tightly linked views of production parameters with cross-filtering capability support the inspection of factors possibly influencing the product quality. ADAM allows highly responsive forward and backward search in the quality and production parameter space, leading to an understanding of important parameters, and supporting production planning and process improvement. Our approach was designed in an iterative development cycle guided by domain requirements from a major aluminum producer. We introduce the domain problem, propose a visual analytics design to support the problem, and demonstrate by application to real production data the usefulness and possible insights which can be obtained., EuroVis 2019 - Posters, Posters, 49, 51, Nikolina Jekic, Belgin Mutlu, Mario Faschang, Steffen Neubert, Stefan Thalmann, and Tobias Schreck, CCS Concepts: Human-centered computing --> Visual Analytics; Data Exploration

Depictions of molecular surfaces such as the Solvent Excluded Surface (SES) can provide crucial insight into functional molecular properties, such as the molecule's potential to react. The interactive visualization of single and multiple molecule surfaces is essential for the data analysis by domain experts. Nowadays, the SES can be rendered at high frame rates using shader-based ray casting on the GPU. However, rendering large molecules or larger molecule complexes requires large amounts of memory that has the potential to exceed the memory limitations of current hardware. Here we show that rendering using CPU ray tracing also reaches interactive frame rates without hard limitations to memory. In our results large molecule complexes can be rendered with only the precomputation of each individual SES, and no further involved representation or transformation. Additionally, we provide advanced visualization techniques like ambient occlusion opacity mapping (AOOM) to enhance the comprehensibility of the molecular structure. CPU ray tracing not only provides very high image quality and global illumination, which is beneficial for the perception of spatial structures, it also opens up the possibility to visualize larger data sets and to render on any HPC cluster. Our results demonstrate that simple instancing of geometry keeps the memory consumption for rendering large molecule complexes low, so the examination of much larger data is also possible., Eurographics Workshop on Visual Computing for Biology and Medicine, Molecular Visualization (II), 239, 251, Tobias Rau, Sebastian Zahn, Michael Krone, Guido Reina, and Thomas Ertl, CCS Concepts: Human-centered computing --> Scientific visualization; Computing methodologies --> Ray tracing; Applied computing --> Molecular structural biology

In-situ visualization and analysis is a powerful concept that aims to give users the ability to process data while it is still resident in memory, thereby vastly reducing the amount of data left for post-hoc analysis. The problem of having too much data for posthoc analysis is exacerbated in large-scale high-performance computing applications such as Nek5000, a massively-parallel CFD (Computational Fluid Dynamics) code used primarily for thermal hydraulics problems. Specifically, one problem users of Nek5000 often face is validating the mesh, that is identifying the exact location of problematic mesh elements within the whole mesh. Employing the standard post-hoc approach to address this problem is both time consuming and requires vast storage space. In this paper, we demonstrate how in-situ visualization, produced with SENSEI, a generic in-situ platform, helps users quickly validate the mesh. We also provide a bridge between Nek5000 and SENSEI that enables users to use any existing and future analysis routines in SENSEI. The approach is evaluated on a number of realistic datasets., Eurographics Symposium on Parallel Graphics and Visualization, Session 1, 7, 16, Sergei Shudler, Nicola Ferrier, Joseph Insley, Michael E. Papka, Saumil Patel, and Silvio Rizzi, CCS Concepts: Human-centered computing --> Visualization systems and tools; Computing methodologies --> Massively parallel and high-performance simulations; General and reference --> Performance