Surface Extraction from Multi-field Particle Volume Data Using Multi-dimensional Cluster Visualization

Data sets resulting from physical simulations typically contain a multitude of physical variables. It is, therefore, desirable that visualization methods take into account the entire multi-field volume data rather than concentrating on one variable. We present a visualization approach based on surface extraction from multi-field particle volume data. The surfaces segment the data with respect to the underlying multi-variate function. Decisions on segmentation properties are based on the analysis of the multi-dimensional feature space. The feature space exploration is performed by an automated multi-dimensional hierarchical clustering method, whose resulting density clusters are shown in the form of density level sets in a 3D star coordinate layout. In the star coordinate layout, the user can select clusters of interest. A selected cluster in feature space corresponds to a segmenting surface in object space. Based on the segmentation property induced by the cluster membership, we extrac...

• Type: Conference
• Year: 2008
• Where: VIS
• Authors: Lars Linsen, Tran Van Long, Paul Rosenthal, Stephan Rosswog
• Keywords: Extracted Surface Points, IEEE Visualization, Particle Volume Data, Point-based Volume Data, VIS 2008, Visualization