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Linking and brushing is a proven approach to analyzing multi-dimensional datasets in the context of multiple coordinated views. Nevertheless, most of the respective visualization techniques only offer qualitative visual results. Many user tasks, however, also require precise quantitative results as, for example, offered by statistical analysis. In succession of the useful Rank-by-Feature Framework,...
Feature-based flow visualization is naturally dependent on feature extraction. To extract flow features, often higher order properties of the flow data are used such as the Jacobian or curvature properties, implicitly describing the flow features in terms of their inherent flow characteristics (for example, collinear flow and vorticity vectors). In this paper, we present recent research that leads...
In this paper we discuss the application of multiple linked views for advanced vortex investigation in flow data. Local feature detectors and additional measures integrate into an interactive flow feature detection system based on multiple linked views. We discuss how linking and brushing of derived feature information can lead to increased performance in interactive feature analysis. In a case study...
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