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Issue No.09 - Sept. (2012 vol.18)
pp: 1397-1410
Xiaoru Yuan , Key Lab. of Machine Perception, Peking Univ., Beijing, China
ABSTRACT
In this paper, we present an effective and scalable system for multivariate volume data visualization and analysis with a novel transfer function interface design that tightly couples parallel coordinates plots (PCP) and MDS-based dimension projection plots. In our system, the PCP visualizes the data distribution of each variate (dimension) and the MDS plots project features. They are integrated seamlessly to provide flexible feature classification without context switching between different data presentations during the user interaction. The proposed interface enables users to identify relevant correlation clusters and assign optical properties with lassos, magic wand, and other tools. Furthermore, direct sketching on the volume rendered images has been implemented to probe and edit features. With our system, users can interactively analyze multivariate volumetric data sets by navigating and exploring feature spaces in unified PCP and MDS plots. To further support large-scale multivariate volume data visualization and analysis, Scalable Pivot MDS (SPMDS), parallel adaptive continuous PCP rendering, as well as parallel rendering techniques are developed and integrated into our visualization system. Our experiments show that the system is effective in multivariate volume data visualization and its performance is highly scalable for data sets with different sizes and number of variates.
INDEX TERMS
rendering (computer graphics), data visualisation, pattern classification, parallel adaptive continuous PCP rendering, scalable multivariate volume visualization, dimension projection, parallel coordinates, multivariate volume data visualization, transfer function interface design, parallel coordinates plots, MDS-based dimension projection plots, flexible feature classification, context switching, data presentations, user interaction, optical properties, lassos, magic wand, direct sketching, volume rendered images, multivariate volumetric data sets, MDS plots, PCP plots, scalable pivot MDS, Data visualization, Rendering (computer graphics), Transfer functions, Algorithm design and analysis, Vegetation, Correlation, parallel visualization., Multivariate volume, transfer function, parallel coordinates, dimension projection, user-interface design
CITATION
Xiaoru Yuan, "Scalable Multivariate Volume Visualization and Analysis Based on Dimension Projection and Parallel Coordinates", IEEE Transactions on Visualization & Computer Graphics, vol.18, no. 9, pp. 1397-1410, Sept. 2012, doi:10.1109/TVCG.2012.80
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