Intelligent cutaway illustrations

Artistic illustrations of important structures in fluid flow have a long-standing tradition and are appreciated as clearly perceivable, instructive, but still conveying all relevant information to the viewer. One important illustrative technique for such visualizations are cutaways. Currently cutaways are placed manually or using view-vector based approaches. We propose to optimize the visibility of important target features based on a degree-of-interest (DOI) function. The DOI is specified during interactive visual analysis, e.g., by brushing scatterplots. We show that the problem of placing cutaway boxes optimally is NP-hard in the number of boxes. To overcome this obstacle, we present an intelligent method to compute cutaways. Geometric cutaway objects are positioned using a view-dependent objective function which optimizes the visibility of all features. In order to approximate the optimal solution, we use a Monte Carlo method and exploit temporal coherence in dynamic scenes. Performance-critical parts are implemented on the GPU. The proposed method can be integrated easily into existing rendering frameworks and is general enough to be able to optimize other parameters besides cutaways as well. We evaluate the performance of the algorithm and provide a case study of vorticity visualization in a turbulent flow.