Similarity-based exploded views

Abstract

Exploded views are often used in illustration to overcome the problem of occlusion when depicting complex structures. In this paper, we propose a volume visualization technique inspired by exploded views that partitions the volume into a number of parallel slabs and shows them apart from each other. The thickness of slabs is driven by the similarity between partitions. We use an information-theoretic technique for the generation of exploded views. First, the algorithm identifies the viewpoint which gives the most structured view of the data. Then, the partition of the volume into the most informative slabs for exploding is obtained using two complementary similarity-based strategies. The number of slabs and the similarity parameter are freely adjustable by the user

This work has been supported by TIN2007-68066-C04-01 and TIN2007-67982-C02 of the Ministry of Education and Science (Spanish Government), by the MedViz Initiative in Bergen (medviz.uib.no), and by the Austrian Science Fund (FWF) grant no. P18322