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- Ronald Peikert, Martin Roth
- IEEE Visualization
- 1999

In this paper we propose an elementary operation on a pair of vector fields as a building block for defining and computing global line–type features of vector or scalar fields. While usual feature definitions often are procedural and therefore implicit, our operator allows precise mathematical definitions. It can serve as a basis for comparing feature… (More)

- Dirk Bauer, Ronald Peikert
- VisSym
- 2002

Automatic extraction of features is a promising strategy to cope with the large amount of data produced by time-dependent CFD (computational fluid dynamics) simulations. Computation time for this type of simulations is typically in the order of days, which justifies the time spent on post-processing the data by extracting features in a batch run. Automatic… (More)

- Filip Sadlo, Ronald Peikert
- IEEE Transactions on Visualization and Computer…
- 2007

This paper presents a method for filtered ridge extraction based on adaptive mesh refinement. It is applicable in situations where the underlying scalar field can be refined during ridge extraction. This requirement is met by the concept of Lagrangian coherent structures which is based on trajectories started at arbitrary sampling grids that are independent… (More)

- Martin Roth, Ronald Peikert
- IEEE Visualization
- 1998

This paper presents a novel method to extract vortical structures from 3D CFD vector fields automatically. It discusses the underlying theory and some aspects of the implementation. Making use of higher-order derivatives, the method is able to locate bent vortices. In order to structure the recognition procedure, we distinguish locating the core line from… (More)

- Ronald Peikert, Filip Sadlo
- PacificVis
- 2008

Motivated by the growing interest in the use of ridges in scientific visualization, we analyze the two height ridge definitions by Eberly and Lindeberg. We propose a raw feature definition leading to a superset of the ridge points as obtained by these two definitions. The set of raw feature points has the correct dimensionality, and it can be narrowed down… (More)

- Martin Roth, Ronald Peikert
- IEEE Visualization
- 1996

Visualization of CFD data for turbomachinery design poses some special requirements which are often not addressed by standard flow visualization systems. We discuss the issues involved with this particular application and its requirements with respect to flow visualization. Aiming at a feature-based visualization for this task, we will examine various… (More)

- Filip Sadlo, Tim Weyrich, Ronald Peikert, Markus H. Gross
- SPBG
- 2005

We present a simple and high-quality 3D scanning system based on structured light. It uses the common setup of a video projector, a computer-controlled turntable and a single camera. Geometry is acquired using a combination of Gray code and phase-shift projections, and it is stored and processed in a point-based representation. We achieve high accuracy by… (More)

- Ovidio Mallo, Ronald Peikert, Christian Sigg, Filip Sadlo
- IEEE Visualization
- 2005

For the rendering of vector and tensor fields, several texturebased volumetric rendering methods were presented in recent years. While they have indisputable merits, the classical vertex-based rendering of integral curves has the advantage of better zooming capabilities as it is not bound to a fixed resolution. It has been shown that lighting can improve… (More)

This paper takes a look at the visualization side of vector field analysis based on Lagrangian coherent structures. The Lagrangian coherent structures are extracted as height ridges of finite-time Lyapunov exponent fields. The resulting visualizations are compared to those from traditional instantaneous vector field topology of steady and unsteady vector… (More)

- Tony McLoughlin, Robert S. Laramee, Ronald Peikert, Frits H. Post, Min Chen
- Comput. Graph. Forum
- 2009

Flow visualization is a fascinating sub-branch of scientific visualization. With ever increasing computing power, it is possible to process ever more complex fluid simulations. However, a gap between data set sizes and our ability to visualize them remains. This is especially true for the field of flow visualization which deals with large, timedependent,… (More)