Adaptive Grid Generation for Volume Representation

Abstract

Recent advances in volume scanning techniques have made the task of acquiring volume data of 3-D objects easier and more accurate. Since the quantity of such acquired data is generally very large, a volume model capable of compressing data while maintaining a specified accuracy is required. The objective of this work is to construct a multi resolution tetrahedral representation of input volume data. This representation adapts to local field properties while preserving their discontinuities. In this paper, we present an accuracy-based adaptive sampling and reconstruction technique. We have developed a parallel algorithm of adaptive grid generation, according to local field properties and such as orientation and curvature of isosurfaces, until the entire volume has been approximated within a specified level of view-invariant accuracy. Experimental results demonstrate the validity and effectiveness of the proposed approach.