An Automated Approach for Slicing Plane Placement in Visual Data Analysis

Effective display and visual analysis of complex 3D data is a challenging task. Occlusions, overlaps, and projective distortions-as frequently caused by typical 3D rendering techniques-can be major obstacles to unambiguous and robust data analysis. Slicing planes are a ubiquitous tool to resolve several of these issues. They act as simple clipping geometry to provide clear cut-away views of the data. We propose to enhance the visualization and analysis process by providing methods for automatic placement of such slicing planes based on local optimization of gradient vector flow. The final obtained slicing planes maximize the total amount of information displayed with respect to a pre-specified importance function. We demonstrate how such automated slicing plane placement is able to support and enrich 3D data visualization and analysis in multiple scenarios, such as volume or surface rendering, and evaluate its performance in several benchmark data sets.