Browsing by Author "Diehl, Alexandra"

Now showing 1 - 5 of 5
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    DanceMoves: A Visual Analytics Tool for Dance Movement Analysis
    (The Eurographics Association, 2021) Arpatzoglou, Vasiliki; Kardara, Artemis; Diehl, Alexandra; Flueckiger, Barbara; Helmer, Sven; Pajarola, Renato; Agus, Marco and Garth, Christoph and Kerren, Andreas
    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.
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    Hornero: Thunderstorms Characterization using Visual Analytics
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Diehl, Alexandra; Pelorosso, Rodrigo; Ruiz, Juan; Pajarola, Renato; Gröller, M. Eduard; Bruckner, Stefan; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
    Analyzing the evolution of thunderstorms is critical in determining the potential for the development of severe weather events. Existing visualization systems for short-term weather forecasting (nowcasting) allow for basic analysis and prediction of storm developments. However, they lack advanced visual features for efficient decision-making. We developed a visual analytics tool for the detection of hazardous thunderstorms and their characterization, using a visual design centered on a reformulated expert task workflow that includes visual features to overview storms and quickly identify high-impact weather events, a novel storm graph visualization to inspect and analyze the storm structure, as well as a set of interactive views for efficient identification of similar storm cells (known as analogs) in historical data and their use for nowcasting. Our tool was designed with and evaluated by meteorologists and expert forecasters working in short-term operational weather forecasting of severe weather events. Results show that our solution suits the forecasters' workflow. Our visual design is expressive, easy to use, and effective for prompt analysis and quick decision-making in the context of short-range operational weather forecasting.
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    LOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2020) Amiraghdam, Alireza; Diehl, Alexandra; Pajarola, Renato; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
    Visualization of large vector line data is a core task in geographic and cartographic systems. Vector maps are often displayed at different cartographic generalization levels, traditionally by using several discrete levels-of-detail (LODs). This limits the generalization levels to a fixed and predefined set of LODs, and generally does not support smooth LOD transitions. However, fast GPUs and novel line rendering techniques can be exploited to integrate dynamic vector map LOD management into GPU-based algorithms for locally-adaptive line simplification and real-time rendering. We propose a new technique that interactively visualizes large line vector datasets at variable LODs. It is based on the Douglas-Peucker line simplification principle, generating an exhaustive set of line segments whose specific subsets represent the lines at any variable LOD. At run time, an appropriate and view-dependent error metric supports screen-space adaptive LOD levels and the display of the correct subset of line segments accordingly. Our implementation shows that we can simplify and display large line datasets interactively. We can successfully apply line style patterns, dynamic LOD selection lenses, and anti-aliasing techniques to our line rendering.
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    LOOPS: LOcally Optimized Polygon Simplification
    (The Eurographics Association and John Wiley & Sons Ltd., 2022) Amiraghdam, Alireza; Diehl, Alexandra; Pajarola, Renato; Borgo, Rita; Marai, G. Elisabeta; Schreck, Tobias
    Displaying polygonal vector data is essential in various application scenarios such as geometry visualization, vector graphics rendering, CAD drawing and in particular geographic, or cartographic visualization. Dealing with static polygonal datasets that has a large scale and are highly detailed poses several challenges to the efficient and adaptive display of polygons in interactive geographic visualization applications. For linear vector data, only recently a GPU-based level-of-detail (LOD) polyline simplification and rendering approach has been presented which can perform locally-adaptive LOD visualization of large-scale line datasets interactively. However, locally optimized LOD simplification and interactive display of large-scale polygon data, consisting of filled vector line loops, remains still a challenge, specifically in 3D geographic visualizations where varying LOD over a scene is necessary. Our solution to this challenge is a novel technique for locally-optimized simplification and visualization of 2D polygons over a 3D terrain which features a parallelized point-inside-polygon testing mechanism. Our approach is capable of employing any simplification algorithm that sequentially removes vertices such as Douglas-Peucker and Wang-Müller. Moreover, we generalized our technique to also visualizing polylines in order to have a unified method for displaying both data types. The results and performance analysis show that our new algorithm can handle large datasets containing polygons composed of millions of segments in real time, and has a lower memory demand and higher performance in comparison to prior methods of line simplification and visualization.
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    VisGuided: A Community-driven Approach for Education in Visualization
    (The Eurographics Association, 2021) Diehl, Alexandra; Firat, Elif E.; Torsney-Weir, Thomas; Abdul-Rahman, Alfie; Bach, Benjamin; Laramee, Robert; Pajarola, Renato; Chen, Min; Sousa Santos, Beatriz and Domik, Gitta
    We propose a novel educational approach for teaching visualization, using a community-driven and participatory methodology that extends the traditional course boundaries from the classroom to the broader visualization community.We use a visualization community project, VisGuides, as the main platform to support our educational approach. We evaluate our new methodology by means of three use cases from two different universities. Our contributions include the proposed methodology, the discussion on the outcome of the use cases, the benefits and limitations of our current approach, and a reflection on the open problems and noteworthy gaps to improve the current pedagogical techniques to teach visualization and promote critical thinking. Our findings show extensive benefits from the use of our approach in terms of the number of transferable skills to students, educational resources for educators, and additional feedback for research opportunities to the visualization community.