Column-based cluster and bar axis density in parallel coordinates
Proceedings of the 3rd International Symposium on Visual Information Communication
Quantitative data visualization with interactive KDE surfaces
Proceedings of the 26th Spring Conference on Computer Graphics
Techniques for precision-based visual analysis of projected data
Information Visualization - Special issue on selected papers from visualization and data analysis 2010
Information Visualization - Special issue on selected papers from visualization and data analysis 2010
Automating Transfer Function Design with Valley Cell-Based Clustering of 2D Density Plots
Computer Graphics Forum
Hybrid parallelization for multi-view visualization of time-dependent simulation data
EG PGV'09 Proceedings of the 9th Eurographics conference on Parallel Graphics and Visualization
ExtractVis: dynamic visualization of extracting multidimensional data
Proceedings of the 5th International Symposium on Visual Information Communication and Interaction
Efficient and adaptive rendering of 2-D continuous scatterplots
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Visual coherence for large-scale line-plot visualizations
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Progressive splatting of continuous scatterplots and parallel coordinates
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Uncertainty-aware exploration of continuous parameter spaces using multivariate prediction
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
A gradient-based comparison measure for visual analysis of multifield data
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Continuous representation of projected attribute spaces of multifields over any spatial sampling
EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization
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Scatterplots are well established means of visualizing discrete data values with two data variables as a collection of discrete points. We aim at generalizing the concept of scatterplots to the visualization of spatially continuous input data by a continuous and dense plot. An example of a continuous input field is data defined on an n-D spatial grid with respective interpolation or reconstruction of in-between values. We propose a rigorous, accurate, and generic mathematical model of continuous scatterplots that considers an arbitrary density defined on an input field on an n-D domain and that maps this density to m-D scatterplots. Special cases are derived from this generic model and discussed in detail: scatterplots where the n-D spatial domain and the m-D data attribute domain have identical dimension, 1-D scatterplots as a way to define continuous histograms, and 2-D scatterplots of data on 3-D spatial grids. We show how continuous histograms are related to traditional discrete histograms and to the histograms of isosurface statistics. Based on the mathematical model of continuous scatterplots, respective visualization algorithms are derived, in particular for 2-D scatterplots of data from 3-D tetrahedral grids. For several visualization tasks, we show the applicability of continuous scatterplots. Since continuous scatterplots do not only sample data at grid points but interpolate data values within cells, a denseand complete visualization of the data set is achieved that scales well with increasing data set size. Especially for irregular grids with varying cell size, improved results are obtained when compared to conventional scatterplots. Therefore, continuous scatterplots are a suitable extension of a statistics visualization technique to be applied to typical data from scientific computation.