Abstract The analysis of unsteady phenomena is an important topic for scientific visualization. Several time‐dependent visualization techniques exist, as well as solutions for dealing with the enormous size of time‐varying data in interactive visualization. Many current visualization toolkits support displaying time‐varying data sets. However, for the interactive exploration of time‐varying data in scientific visualization, no common time model that describes the temporal properties which occur in the visualization process has been established. In this work, we propose a general time model which classifies the time frames of simulation phenomena and the connections between different time scales in the analysis process. This model is designed for intuitive interaction with time in visualization applications for the domain expert as well as for the developer of visualization tools. We demonstrate the benefits of our model by applying it to two use cases with different temporal properties.

We propose a method to determine the optimal camera alignment for a tracking system with multiple cameras by specifying the volume to be tracked and an initial camera setup. We use optimization strategies based on methods usually employed for solving nonlinear systems of equations. All approaches are fully automatic and take advantage of modern graphics hardware since we also implement a GPU-based, accelerated visibility test. The algorithm automatically optimizes the whole setup by adjusting the given set of camera parameters. We can steer the optimization towards different goals depending on the desired application, e.g. the widest possible volume coverage or maximum camera visibility to overcome heavy occlusion problems during the tracking process. We also consider parameter constraints that the user may specify according to restrictions in the local environment where the cameras have to be mounted. This allows for a convenient definition of higher level constraints for the camera setup.