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

Schlegel, Steven; Goldau, Mathias; Scheuermann, Gerik

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

Files

049-056.pdf (4.76 MB)

Date

2015

Authors

Schlegel, Steven
Goldau, Mathias
Scheuermann, Gerik

Publisher

The Eurographics Association

Abstract

We 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.

        @inproceedings{10.2312:vmv.20151257
,
booktitle = {Vision, Modeling & Visualization
},
editor = {David Bommes and Tobias Ritschel and Thomas Schultz
},
title = {{Interactive GPU-based Visualization of Scalar Data with Gaussian Distributed Uncertainty
}},
author = {Schlegel, Steven and 
Goldau, Mathias and 
Scheuermann, Gerik
},
year = {2015
},
publisher = {The Eurographics Association
},
ISBN = {978-3-905674-95-8
},
DOI = {10.2312/vmv.20151257
}
}