Volumetric data exploration using interval volume

Abstract

A new type of geometric model called Interval volume for volumetric data exploration is presented. An interval volume represents a three dimensional subvolume for which the associate scalar values lie within a user specified interval, and provides one of the promising approaches to solid fitting, which is an extended concept of traditional surface fitting. A well known isosurfacing algorithm called Marching Cubes is extended to obtain a solid fitting algorithm, which extracts from a given volumetric data set a high resolution, polyhedral solid data structure of an interval volume. Branch-on-Need Octree is used as an auxiliary data structure to accelerate the extraction process. A variety of interval volume rendering methods and principal related operations, including measurements and focusing, are also presented. The effectiveness of measurement coupled visualization capabilities of the presented approach is demonstrated by application to visualizing a four dimensional simulated data from atomic collision research.