@article {857,
	title = {Accurate and reliable extraction of surfaces from image data using a multi-dimensional uncertainty model},
	volume = {Volume 99},
	year = {2018},
	chapter = {Pages 13},
	abstract = {Surface extraction is an important step in the image processing pipeline to estimate the size and shape of an object. Unfortunately, state of the art surface extraction algorithms form a straight forward extraction based on a pre-defined value that can lead to surfaces, that are not accurate. Furthermore, most isosurface extraction algorithms lack the ability to communicate uncertainty originating from the image data. This can lead to a rejection of such algorithms in many applications. To solve this problem, we propose a methodology to extract and optimize surfaces from image data based on a defined uncertainty model. To identify optimal parameters, the presented method defines a parameter space that is evaluated and rates each extraction run based on the remaining surface uncertainty. The resulting surfaces can be explored intuitively in an interactive framework. We applied our methodology to a variety of datasets to demonstrate the quality of the resulting surfaces.},
	author = {Gillmann, Christina and Wischgoll, Thomas and Hamann, Bernd and Hagen, Hans}
}
@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}
}
@conference {860,
	title = {Visual Analytics of Cascaded Bottlenecks in Planar Flow Networks},
	booktitle = {LEVIA 2018},
	year = {2018},
	abstract = {
Finding bottlenecks and eliminating them to increase the overall flow of a network often appears in real world applications, such as production planning, factory layout, flow related physical approaches, and even cyber security. In many cases, several edges can form a bottleneck (cascaded bottlenecks). This work presents a visual analytics methodology to analyze these cascaded bottlenecks. The methodology consists of multiple steps: identification of bottlenecks, identification of potential improvements, communication of bottlenecks, interactive adaption of bottlenecks, and a feedback loop that allows users to adapt flow networks and their resulting bottlenecks until they are satisfied with the flow network configuration. To achieve this, the definition of a minimal cut is extended to identify network edges that form a (cascaded) bottleneck. To show the effectiveness of the presented approach, we applied the methodology to two flow network setups and show how the overall flow of these networks can be improved.},
	author = {Post, Tobias and Gillmann, Christina and Wischgoll, Thomas and Hamann, Bernd and Hagen, Hans}
}
@article {861,
	title = {An Industrial Vision System to Analyze the Wear of Cutting Tools},
	journal = {Applied Mechanics and Materials},
	volume = {869},
	year = {2017},
	abstract = {The wear behavior of cutting tools directly affects the quality of the machined part. The measurement and evaluation of wear is a time consuming and process and is subjective. Therefore, an image-based wear measure that can be computed automatically based on given image series of cutting tools and an objective way to review the resulting wear is presented in this paper. The presented method follows the industrial vision system pipeline where images of cutting tools are used as input which are then transformed through suitable image processing methods to prepare them for the computation of a novel image based wear measure. For multiple cutting tool settings a comparative visualization of the wear measure outputs is presented. The effectiveness of the presented approach is shown by applying the method to measure the wear of four different cutting tool shapes.},
	author = {Gillmann, Christina and Post, Tobias and Kirsch, Benjamin and Wischgoll, Thomas and J{\"o}rg, Hartig and Hamann, Bernd and Hagen, Hans and Aurich, Christian}
}
