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Item Large Scale Comprehensive 3D Shape Retrieval(The Eurographics Association, 2014) Li, B.; Lu, Y.; Li, C.; Godil, A.; Schreck, Tobias; Aono, M.; Chen, Q.; Chowdhury, N. K.; Fang, B.; Furuya, T.; Johan, H.; Kosaka, R.; Koyanagi, H.; Ohbuchi, R.; Tatsuma, A.; Benjamin Bustos and Hedi Tabia and Jean-Philippe Vandeborre and Remco VeltkampThe objective of this track is to evaluate the performance of 3D shape retrieval approaches on a large-scale comprehensive 3D shape database that contains different types of models, such as generic, articulated, CAD and architecture models. The track is based on a new comprehensive 3D shape benchmark, which contains 8,987 triangle meshes that are classified into 171 categories. The benchmark was compiled as a superset of existing benchmarks and presents a new challenge to retrieval methods as it comprises generic models as well as domainspecific model types. In this track, 14 runs have been submitted by 5 groups and their retrieval accuracies were evaluated using 7 commonly used performance metrics.Item Personalized Visual-Interactive Music Classification(The Eurographics Association, 2018) Ritter, Christian; Altenhofen, Christian; Zeppelzauer, Matthias; Kuijper, Arjan; Schreck, Tobias; Bernard, Jürgen; Christian Tominski and Tatiana von LandesbergerWe present an interactive visual music classification tool that will allow users to automatically structure music collections in a personalized way. With our approach, users play an active role in an iterative process of building classification models, using different interactive interfaces for labeling songs. The interactive tool conflates interfaces for the detailed analysis at different granularities, i.e., audio features, music songs, as well as classification results at a glance. Interactive labeling is provided with three complementary interfaces, combining model-centered and human-centered labeling-support principles. A clean visual design of the individual interfaces depicts complex model characteristics for experts, and indicates our work-inprogress towards the abilities of non-experts. The result of a preliminary usage scenario shows that, with our system, hardly any knowledge about machine learning is needed to create classification models of high accuracy with less than 50 labels.Item SHREC'13 Track: Large-Scale Partial Shape Retrieval Using Simulated Range Images(The Eurographics Association, 2013) Sipiran, I.; Meruane, R.; Bustos, B.; Schreck, Tobias; Johan, H.; Li, B.; Lu, Y.; Umberto Castellani and Tobias Schreck and Silvia Biasotti and Ioannis Pratikakis and Afzal Godil and Remco VeltkampPartial shape retrieval is a challenging problem in content-based 3D model retrieval. This track intends to evaluate the performance of existing algorithms for partial retrieval. The contest is based on a new large-scale query set obtained by mimicking the range image acquisition using a standard 3D benchmark as target set. The query set contains 7200 partial meshes with different levels of complexity. Furthermore, we propose the use of new performance measures based on a partiality factor. With this characteristics, our goal is to evaluate several important aspects: effectiveness, efficiency, robustness and scalability. The obtained results of this track open new questions regarding the difficulty of the partial shape retrieval problem and the scalability of algorithms. In addition, potential future directions on this topic are identified.Item Elastic Flattening of Painted Pottery Surfaces(The Eurographics Association, 2018) Preiner, Reinhold; Karl, Stephan; Bayer, Paul; Schreck, Tobias; Sablatnig, Robert and Wimmer, MichaelGenerating flat images from paintings on curved surfaces is an important task in Archaeological analysis of ancient pottery. It allows comparing styles and painting techniques, e.g, for style and workshop attribution, and serves as basis for domain publications which typically use 2d images. To obtain such flat images from scanned textured 3d models of the pottery objects, current practice is to perform so-called rollouts using approximating shape primitives like cones or spheres, onto which the mesh surfaces are projected. While this process provides in intuitive deformation metaphor for the users, it naturally introduces unwanted distortions in the mapping of the surface, especially for vessels with high-curvature profiles. In this work, we perform an elastic flattening of these projected meshes, where stretch energy is minimized by simulating a physical relaxation process on a damped elastic spring model. We propose an intuitive contraction-directed physical setup which allows for an efficient relaxation while ensuring a controlled convergence. Our work has shown to produce images of significantly improved suitability for domain experts' tasks like interpretation, documentation and attribution of ancient pottery.Item Interactive Analysis of Object Group Changes over Time(The Eurographics Association, 2011) Bremm, S.; Landesberger, T. von; Andrienko, G.; Andrienko, N.; Schreck, Tobias; Silvia Miksch and Giuseppe SantucciThe analysis of time-dependent data is an important task in various application domains. Often, the analyzed data objects belong to groups. The group memberships may stem from natural arrangements (e.g., animal herds), or may be constructed during analysis (e.g., by clustering). Group membership may change over time. Therefore, one important analytical aspect is to examine these changes (e.g., which herds change members and when). In this paper, we present a technique for visual analysis of group changes over time. We combine their visualization and automatic analysis. Interactive functions allow for tracking the data changes over time on group, set and individual level. We also consider added and removed objects (e.g., newly born or died animals). For large time series, automatic data analysis selects interesting time points and group changes for detailed examination. We apply our approach on the VAST 2008 challenge data set revealing new insights.Item Eurographics 2010 Workshop on 3D Object Retrieval (EG 3DOR’10) in cooperation with ACM SIGGRAPH(The Eurographics Association and Blackwell Publishing Ltd., 2011) Daoudi, Mohamed; Schreck, Tobias; Eduard Groeller and Holly RushmeierItem Interactive Visual Exploration of Local Patterns in Large Scatterplot Spaces(The Eurographics Association and John Wiley & Sons Ltd., 2018) Chegini, Mohammad; Shao, Lin; Gregor, Robert; Lehmann, Dirk Joachim; Andrews, Keith; Schreck, Tobias; Jeffrey Heer and Heike Leitte and Timo RopinskiAnalysts often use visualisation techniques like a scatterplot matrix (SPLOM) to explore multivariate datasets. The scatterplots of a SPLOM can help to identify and compare two-dimensional global patterns. However, local patterns which might only exist within subsets of records are typically much harder to identify and may go unnoticed among larger sets of plots in a SPLOM. This paper explores the notion of local patterns and presents a novel approach to visually select, search for, and compare local patterns in a multivariate dataset. Model-based and shape-based pattern descriptors are used to automatically compare local regions in scatterplots to assist in the discovery of similar local patterns. Mechanisms are provided to assess the level of similarity between local patterns and to rank similar patterns effectively. Moreover, a relevance feedback module is used to suggest potentially relevant local patterns to the user. The approach has been implemented in an interactive tool and demonstrated with two real-world datasets and use cases. It supports the discovery of potentially useful information such as clusters, functional dependencies between variables, and statistical relationships in subsets of data records and dimensions.Item Revisiting Perceptually Optimized Color Mapping for High-Dimensional Data Analysis(The Eurographics Association, 2014) Mittelstädt, Sebastian; Bernard, Jürgen; Schreck, Tobias; Steiger, Martin; Kohlhammer, Jörn; Keim, Daniel A.; N. Elmqvist and M. Hlawitschka and J. KennedyColor is one of the most effective visual variables since it can be combined with other mappings and encodeinformation without using any additional space on the display. An important example where expressing additionalvisual dimensions is direly needed is the analysis of high-dimensional data. The property of perceptual linearity isdesirable in this application, because the user intuitively perceives clusters and relations among multi-dimensionaldata points. Many approaches use two-dimensional colormaps in their analysis, which are typically created byinterpolating in RGB, HSV or CIELAB color spaces. These approaches share the problem that the resulting colorsare either saturated and discriminative but not perceptual linear or vice versa. A solution that combines bothadvantages has been previously introduced by Kaski et al.; yet, this method is to date underutilized in InformationVisualization according to our literature analysis. The method maps high-dimensional data points into the CIELABcolor space by maintaining the relative perceived distances of data points and color discrimination. In this paper,we generalize and extend the method of Kaski et al. to provide perceptual uniform color mapping for visual analysisof high-dimensional data. Further, we evaluate the method and provide guidelines for different analysis tasks.Item Visual Analysis of Aluminum Production Data with Tightly Linked Views(The Eurographics Association, 2019) Jekic, Nikolina; Mutlu, Belgin; Faschang, Mario; Neubert, Steffen; Thalmann, Stefan; Schreck, Tobias; Madeiras Pereira, João and Raidou, Renata GeorgiaMonitoring, 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.Item Visual Analysis of Urban Traffic Data based on High-Resolution and High-Dimensional Environmental Sensor Data(The Eurographics Association, 2018) Häußler, Johannes; Stein, Manuel; Seebacher, Daniel; Janetzko, Halldor; Schreck, Tobias; Keim, Daniel; Karsten Rink and Dirk Zeckzer and Roxana Bujack and Stefan JänickeUrbanization is an increasing global trend resulting in a strong increase in public and individual transportation needs. Accordingly, a major challenge for traffic and urban planners is the design of sustainable mobility concepts to maintain and increase the long-term health of humans by reducing environmental pollution. Recent developments in sensor technology allow the precise tracking of vehicle sensor information, allowing a closer and more in-depth analysis of traffic data. We propose a visual analytics system for the exploration of environmental factors in these high-resolution and high-dimensional mobility sensor data. Additionally, we introduce an interactive visual logging approach to enable experts to cope with complex interactive analysis processes and the problem of the reproducibility of results. The usefulness of our approach is demonstrated via two expert studies with two domain experts from the field of environment-related projects and urban traffic planning.