@conference {855, title = {Modeling and Visualization of Uncertainty-aware Geometry using Multi-variate Normal Distributions}, booktitle = {IEEE Pacific Vis Short Paper Track}, year = {2018}, abstract = {Many applications are dealing with geometric data that are affected by uncertainty. This uncertainty is important to analyze, visualize, and understand. We present a methodology to model uncertain geometry based on multi-variate normal distributions. In addition, we propose a visualization technique to represent a hull for uncertain geometry capturing a user-defined percentage of the underlying uncertain geometry. To show the effectiveness of our approach, we have modeled and visualized uncertain datasets from different applications.}, author = {Gillmann, Christina and Wischgoll, Thomas and Hamann, Bernd and Ahrens James} }