Seed Sets and Search Structures for Accelerated Isocontouring

We present three algorithms for the construction of seed sets, a subset of a cell complex which contains at least one cell for each connected component of each isocontour, for all possible isovalues. Seed sets reduce the storage requirements of high performance search structures for isocontouring, such as the segment tree or the interval tree. The three algorithms determine seed sets with varying properties. The first computes seed sets within a constant factor of the optimal size, requiring O(nlogn) time, where n is the size of the mesh. A more conservative approach computes seed sets of slightly larger size with O(n) processing time, and is very amenable to parallel processing. The seeds produced follow a particular pattern which can be leveraged for performing out-of-core isocontouring, dynamically loading only the data which is necessary from secondary storage or a remote server. A specialized form of the second algorithm for regular grids computes seed sets of intermediate size, with only slightly additional effort and the same computational complexity. We examine the use of three search structures and compare their application to the seed sets and full sets of cells from a variety of computational grids.

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