Interactive GPU-based Visualization of Scalar Data with Gaussian Distributed Uncertainty

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dc.contributor.authorSchlegel, Stevenen_US
dc.contributor.authorGoldau, Mathiasen_US
dc.contributor.authorScheuermann, Geriken_US
dc.contributor.editorDavid Bommes and Tobias Ritschel and Thomas Schultzen_US
dc.date.accessioned2015-10-07T05:13:33Z
dc.date.available2015-10-07T05:13:33Z
dc.date.issued2015en_US
dc.description.abstractWe present a GPU-based approach to visualize samples of normally distributed uncertain, three-dimensional scalar data. Our approach uses a mathematically sound interpolation scheme, i.e., Gaussian process regression. The focus of this work is to demonstrate, that GP-regression can be used for interpolation in practice, despite the high computational costs. The potential of our method is demonstrated by an interactive volume rendering of three-dimensional data, where the gradient estimation is directly computed by the field function without the need of additional sample points of the underlying data. We illustrate our method using three-dimensional data sets of the medical research domain.en_US
dc.description.sectionheadersVisualizationen_US
dc.description.seriesinformationVision, Modeling & Visualizationen_US
dc.identifier.doi10.2312/vmv.20151257en_US
dc.identifier.isbn978-3-905674-95-8en_US
dc.identifier.pages49-56en_US
dc.identifier.urihttps://doi.org/10.2312/vmv.20151257en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectMathematics of Computing [G.1.0]en_US
dc.subjectGeneralen_US
dc.subjectError analysis Mathematics of Computing [G.1.1]en_US
dc.subjectInterpolationen_US
dc.subjectInterpolation formulas Computer Graphics [I.3.3]en_US
dc.subjectPicture/Image Generationen_US
dc.subjectDisplay algorithmsen_US
dc.titleInteractive GPU-based Visualization of Scalar Data with Gaussian Distributed Uncertaintyen_US
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