Footprint evaluation for volume rendering
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
Hierarchical splatting: a progressive refinement algorithm for volume rendering
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Random number generation and quasi-Monte Carlo methods
Random number generation and quasi-Monte Carlo methods
Construction of line densities for parallel coordinate plots
Computing and graphics in statistics
VVS '89 Proceedings of the 1989 Chapel Hill workshop on Volume visualization
Multidimensional Transfer Functions for Interactive Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
Interactive feature specification for focus+context visualization of complex simulation data
VISSYM '03 Proceedings of the symposium on Data visualisation 2003
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
A Parallel Coordinates Style Interface for Exploratory Volume Visualization
IEEE Transactions on Visualization and Computer Graphics
Parallel Coordinates: Visual Multidimensional Geometry and Its Applications
Parallel Coordinates: Visual Multidimensional Geometry and Its Applications
Gaussian Transfer Functions for Multi-Field Volume Visualization
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
On Histograms and Isosurface Statistics
IEEE Transactions on Visualization and Computer Graphics
Handbook of Data Visualization (Springer Handbooks of Computational Statistics)
Handbook of Data Visualization (Springer Handbooks of Computational Statistics)
Revisiting Histograms and Isosurface Statistics
IEEE Transactions on Visualization and Computer Graphics
IEEE Transactions on Visualization and Computer Graphics
Continuous Parallel Coordinates
IEEE Transactions on Visualization and Computer Graphics
Structuring Feature Space: A Non-Parametric Method for Volumetric Transfer Function Generation
IEEE Transactions on Visualization and Computer Graphics
Matching Visual Saliency to Confidence in Plots of Uncertain Data
IEEE Transactions on Visualization and Computer Graphics
An Information-Theoretic Framework for Flow Visualization
IEEE Transactions on Visualization and Computer Graphics
Discontinuities in Continuous Scatter Plots
IEEE Transactions on Visualization and Computer Graphics
Relation-Aware Isosurface Extraction in Multifield Data
IEEE Transactions on Visualization and Computer Graphics
Multi-dimensional reduction and transfer function design using parallel coordinates
VG'10 Proceedings of the 8th IEEE/EG international conference on Volume Graphics
Efficient and adaptive rendering of 2-D continuous scatterplots
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
Splatting the lines in parallel coordinates
EuroVis'09 Proceedings of the 11th 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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Continuous scatterplots and parallel coordinates are used to visualize multivariate data defined on a continuous domain. With the existing techniques, rendering such plots becomes prohibitively slow, especially for large scientific datasets. This paper presents a scalable and progressive rendering algorithm for continuous data plots that allows exploratory analysis of large datasets at interactive framerates. The algorithm employs splatting to produce a series of plots that are combined using alpha blending to achieve a progressively improving image. For each individual frame, splats are obtained by transforming Gaussian density kernels from the 3-D domain of the input dataset to the respective data domain. A closed-form analytic description of the resulting splat footprints is derived to allow pre-computation of splat textures for efficient GPU rendering. The plotting method is versatile because it supports arbitrary reconstruction or interpolation schemes for the input data and the splatting technique is scalable because it chooses splat samples independently from the size of the input dataset. Finally, the effectiveness of the method is compared to existing techniques regarding rendering performance and quality.