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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2018年第1期24卷 542-552页

作者： Matute, Jose Telea, Alexandru C. Linsen, Lars Univ Munster Inst Comp Sci Munster Germany Univ Groningen Johann Bernoulli Inst Math & Comp Sci POB 407 NL-9700 AK Groningen Netherlands

Scatterplot matrices (SPLOMs) are widely used for exploring multidimensional data. Scatterplot diagnostics (scagnostics) approaches measure characteristics of scatterplots to automatically find potentially interesting plots, thereby making SPLOMs more scalable with the dimension count. While statistical measures such as regression lines can capture orientation, and graph-theoretic scagnostics measures can capture shape, there is no scatterplot characterization measure that uses both descriptors. Based on well-known results in shape analysis, we propose a scagnostics approach that captures both scatterplot shape and orientation using skeletons (or medial axes). Our representation can handle complex spatial distributions, helps discovery of principal trends in a multiscale way, scales visually well with the number of samples, is robust to noise, and is automatic and fast to compute. We define skeleton-based similarity metrics for the visual exploration and analysis of SPLOMs. We perform a user study to measure the human perception of scatterplot similarity and compare the outcome to our results as well as to graph-based scagnostics and other visual quality metrics. Our skeleton-based metrics outperform previously defined measures both in terms of closeness to perceptually-based similarity and computation time efficiency.

关键词： Multidimensional data (primary keyword) High-Dimensional data

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What Moves Players? visual data exploration of Twitter and Gameplay data 18

What Moves Players? Visual Data Exploration of Twitter and G...

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CHI conference on Human Factors in Computing Systems (CHI)

作者： Drescher, Christian Wallner, Guenter Kriglstein, Simone Sifa, Rafet Drachen, Anders Pohl, Margit TU Wien Vienna Austria Fraunhofer IAIS St Augustin Germany Univ York DC Labs York N Yorkshire England

ISBN: (纸本)9781450356206

In recent years, microblogging platforms have not only become an important communication channel for the game industry to generate and uphold audience interest but also a rich resource for gauging player opinion. In this paper we use data gathered from Twitter to examine which topics matter to players and to identify influential members of a game's community. By triangulating in-game data with Twitter activity we explore how tweets can provide contextual information for understanding fluctuations in in-game activity. To facilitate analysis of the data we introduce a visual data exploration tool and use it to analyze tweets related to the game Destiny. In total, we collected over one million tweets from about 250,000 users over a 14-month period and gameplay data from roughly 3,500 players over a six-month period.

关键词： Twitter Gameplay data Online Community Destiny

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14th International Symposium on visual Computing, ISVC 2019

14th International Symposium on Visual Computing, ISVC 2019

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14th International Symposium on visual Computing, ISVC 2019

ISBN: (纸本)9783030337193

The proceedings contain 100 papers. The special focus in this conference is on visual Computing. The topics include: Adaptive Attention Model for Lidar Instance Segmentation;view Dependent Surface Material Recognition;3D visual Object Detection from Monocular Images;skin Identification Using Deep Convolutional Neural Network;resolution-Independent Meshes of Superpixels;automatic Video Colorization Using 3D Conditional Generative Adversarial Networks;improving visual Reasoning with Attention Alignment;multi-camera Temporal Grouping for Play/Break Event Detection in Soccer Games;Trajectory Prediction by Coupling Scene-LSTM with Human Movement LSTM;DeepGRU: Deep Gesture Recognition Utility;augmented Curiosity: Depth and Optical Flow Prediction for Efficient exploration;information visualization for Highlighting Conflicts in Educational Timetabling Problems;contourNet: Salient Local Contour Identification for Blob Detection in Plasma Fusion Simulation data;mutual Information-Based Texture Spectral Similarity Criterion;accurate Computation of Interval Volume Measures for Improving Histograms;Ant-SNE: Tracking Community Evolution via Animated t-SNE;Automated Segmentation of the Pectoral Muscle in Axial Breast MR Images;Angio-AI: Cerebral Perfusion Angiography with Machine Learning;conformal Welding for Brain-Intelligence analysis;Learning Graph Cut Class Prototypes for Thigh CT Tissue Identification;delineation of Road Networks Using Deep Residual Neural Networks and Iterative Hough Transform;automatic Estimation of Arterial Input Function in Digital Subtraction Angiography;one-Shot-Learning for visual Lip-Based Biometric Authentication;age Group and Gender Classification of Unconstrained Faces;efficient 3D Face Recognition in Uncontrolled Environment;Pupil Center Localization Using SOMA and CNN;Real-Time Face Features Localization with Recurrent Refined Dense CNN Architectures;estimation of the Distance Between Fingertips Using Silhouette and Texture Information of Dorsa

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exploration of User Groups in VEXUS 34

Exploration of User Groups in VEXUS

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34th IEEE International conference on data Engineering Workshops (ICDEW)

作者： Amer-Yahia, Sihem Omidvar-Tehrani, Behrooz Comba, Joao Moreira, Viviane Zegarra, Fabian Colque Univ Grenoble Alpes Grenoble France CNRS Paris France Univ Fed Rio Grande do Sul Porto Alegre RS Brazil

ISBN: (纸本)9781538655207

We demonstrate VEXUS, an interactive visualization framework for exploring user data to fulfill tasks such as finding a set of experts, forming discussion groups and analyzing collective behaviors. User data is characterized by a combination of demographics like age and occupation, and actions such as rating a movie, writing a paper or following a medical treatment. The ubiquity of user data requires tools that help explorers, be they specialists or novice users, acquire new insights. VEXUS lets explorers interact with user data via visual primitives and builds an exploration profile to recommend the next exploration steps. VEXUS combines state-of-the-art visualization techniques with appropriate indexing of user data to provide fast and relevant exploration.

关键词： data visualization Histograms Navigation Brushes Task analysis visualization Motion pictures

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RescueMark: visual Analytics of Social Media data for Guiding Emergency Response in Disaster Situations: Award for Skillful Integration of Language Model

RescueMark: Visual Analytics of Social Media Data for Guidin...

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IEEE Symposium on visual Analytics Science and Technology (VAST)

作者： Astrik Jeitler Alpin Türkoglu Denis Makarov Timo Jockers Juri Buchmüller Udo Schlegel Daniel A. Keim University of Konstanz Germany

This paper presents RescueMark, a web-based visual analytics tool for analyzing disaster situations and guiding emergency response. In disaster situations operators must take quick and effective decisions to solve critical problems. RescueMark provides spatial, topic and temporal event exploration supporting decision making for resource allocation and determine damaged areas of the city. We describe the data analysis and visualization process of the social media data applied to extract the relevant information.

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Dimensional Morphing Interface for Dynamic Learning Evaluation 22

Dimensional Morphing Interface for Dynamic Learning Evaluati...

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22nd International conference Information visualisation (iv) - Biomedical visualization, visualisation on Built and Rural Environments and Geometric Modelling and Imaging

作者： Franzoni, Valentina Mengoni, Paolo Milani, Alfredo Univ Roma La Sapienza Dept Engn Rome Italy Univ Firenze Dipartimento Matemat & Informat Florence Italy Univ Perugia Dipartimento Matemat & Informat Perugia Italy

ISBN: (纸本)9781538672020

In this paper an innovative dynamic dimensional morphing metaphor is introduced to monitor students' engagement and cohort dynamic. Teachers using eLearning monitoring tools find them usually lacking usability and inadequate to give productive feedback about their learning designs. Learning analytics tools mostly focus on after course analysis with the assumption that user competence in data analysis is high. The tool we propose is based on visual interface morphing: reshaping of the interface elements, such as learning objects' links and icons, is put in place to reflect some key performance indicators of learners' activities. Quantitative and temporal analytics data, aggregated using various functions, is used to present animated enhanced information to teachers. Experiments for the assessment of the effectiveness of the proposed tool has been conducted on data from higher education courses. Through logs' analysis and teachers' questionnaires the usability and validity of the proposed metaphor has been assessed. The proposed tool outperforms traditional monitoring techniques.

关键词： eLearning learner monitoring learning design evaluation visual interfaces usability

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visual ANALYTICS FOR SIMULATION ENSEMBLES 18

VISUAL ANALYTICS FOR SIMULATION ENSEMBLES

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Winter Simulation conference (WSC)

作者： Matkovic, Kresimir Gracanin, Denis Hauser, Helwig VRVis Forsch GmbH Donau City Str 11 A-1220 Vienna Austria Virginia Tech Dept Comp Sci 2202 Kraft Dr Blacksburg VA 24060 USA Univ Bergen Dept Informat Postboks 7803 N-5020 Bergen Norway

ISBN: (纸本)9781538665725

We often simulate multiple variations of the same model - a simulation ensemble - to better understand intricate physical phenomena. The analysis of complex simulation ensembles represents a grand challenge which is approached by both computational and interactive, visual methods. We describe how modern visual analytics helps to analyze simulation ensemble data. A clever combination of computational and interactive methods supports the simulation expert to gain deeper insight into the data and into the physical phenomenon that is represented by the ensemble. An analysis environment that combines interactive visualization and computational analysis provides unique advantages for the exploration and analysis of complex ensemble data. It helps the domain expert to efficiently cope with analysis tasks, in particular when they are only partially defined. In this work, we describe the basics of interactive visual analysis, several approaches to interactive ensemble steering, and means for results quantification and analysis reproducibility.

关键词： Computational modeling Analytical models data models data visualization Valves visual analytics

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Patient-Specific Conditional Joint Models of Shape, Image Features and Clinical Indicators 22nd

Patient-Specific Conditional Joint Models of Shape, Image Fe...

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10th International Workshop on Machine Learning in Medical Imaging (MLMI) / 22nd International conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)

作者： Egger, Bernhard Schirmer, Markus D. Dubost, Florian Nardin, Marco J. Rost, Natalia S. Golland, Polina MIT Comp Sci & Artificial Intelligence Lab CSAIL 77 Massachusetts Ave Cambridge MA 02139 USA Harvard Med Sch Massachusetts Gen Hosp MGH Boston MA 02115 USA German Ctr Neurodegenerat Dis DZNE Bonn Germany Erasmus MC Univ Med Ctr Rotterdam Rotterdam Netherlands

ISBN: (纸本)9783030322519;9783030322502

We propose and demonstrate a joint model of anatomical shapes, image features and clinical indicators for statistical shape modeling and medical image analysis. The key idea is to employ a copula model to separate the joint dependency structure from the marginal distributions of variables of interest. This separation provides flexibility on the assumptions made during the modeling process. The proposed method can handle binary, discrete, ordinal and continuous variables. We demonstrate a simple and efficient way to include binary, discrete and ordinal variables into the modeling. We build Bayesian conditional models based on observed partial clinical indicators, features or shape based on Gaussian processes capturing the dependency structure. We apply the proposed method on a stroke dataset to jointly model the shape of the lateral ventricles, the spatial distribution of the white matter hyperintensity associated with periventricular white matter disease, and clinical indicators. The proposed method yields interpretable joint models for data exploration and patient-specific statistical shape models for medical image analysis.

关键词： Statistical shape modeling Copula Gaussian processes Attributes Meta-data White matter hyperintensities

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12th International conference on Intelligent Robotics and Applications, ICIRA 2019

12th International Conference on Intelligent Robotics and Ap...

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12th International conference on Intelligent Robotics and Applications, ICIRA 2019

ISBN: (纸本)9783030275402

The proceedings contain 378 papers. The special focus in this conference is on Intelligent Robotics and Applications. The topics include: Intelligent Robot Arm: Vision-Based Dynamic Measurement System for Industrial Applications;research on Autonomous Face Recognition System for Spatial Human-Robotic Interaction Based on Deep Learning;KPCA-Based visual Fault Diagnosis for Nonlinear Industrial Process;data Denosing Processing of the Operating State of the Robotic Arm of Coal Sampling Robot;a Study on Step-by-Step Calibration of Robot Based on Multi-vision Measurement;characteristic Frequency Input Neural Network for Inertia Identification of Tumbling Space Target;An FFT-based Method for analysis, Modeling and Identification of Kinematic Error in Harmonic Drives;real-Time Human-Posture Recognition for Human-Drone Interaction Using Monocular Vision;HSVM-Based Human Activity Recognition Using Smartphones;stability analysis and Fixed Radius Turning Planning of Hexapod Robot;Human-AGV Interaction: Real-Time Gesture Detection Using Deep Learning;Coverage Path Planning for Complex Structures Inspection Using Unmanned Aerial Vehicle (UAV);development of Four Rotor Fire Extinguishing System for Synchronized Monitoring of Air and Ground for Fire Fighting;A Small Envelope Gait Control Algorithm Based on FTL Method for Snake-Like Pipe Robot;trajectory Tracking Control of Wheeled Mobile Robots Using Backstepping;the Design of Inspection Robot Navigation Systems Based on Distributed Vision;mobile Robot Autonomous Navigation and Dynamic Environmental Adaptation in Large-Scale Outdoor Scenes;movement analysis of Rotating-Finger Cable Inspection Robot;autonomous Indoor Mobile Robot exploration Based on Wavefront Algorithm;multi-robot Path Planning for Complete Coverage with Genetic Algorithms;the Mechanical Design and Torque Control for the Ankle Exoskeleton During Human Walking.

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Interactive mixed brushing: Integrated text and visual based data exploration 2018

Interactive mixed brushing: Integrated text and visual based...

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2018 Computer Graphics International conference, CGI 2018

作者： Beham, Michael Graanin, Denis Podaras, Silvana Splechtna, Rainer Bühler, Katja Pandi, Igor S. Matkovi, Kreimir VRVis Research Center Vienna Austria Virginia Tech BlacksburgVA United States University of Zagreb Zagreb Croatia

ISBN: (纸本)1595930361

Linking and brushing is an essential technique for interactive data exploration and analysis that leverages coordinated multiple views to identify, select, and combine data points of interest. We propose to augment this technique by directly exploring data space using textual queries. Textual and visual queries are freely combined and modified during the data exploration process. visual queries are used to refine the results of textual queries and vice versa. This mixed brushing integrates procedural, textual, and visual based data exploration to provide a unified approach to brushing. We also propose an interface - - the Text Query Browser View, that allows users to specify and edit data queries as well as to browse the data query history. Further, we argue why an interactive, on-demand, data aggregation and derivation is necessary, and we provide a flexible mechanism that supports it. We have implemented the proposed approach within an existing visualization tool using a client-server architecture. The approach was illustrated and evaluated using two example data sets. © 2018 ACM.

关键词： visualization

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