|AOSC Departmental Seminar
February 18, 2016
Representation and topological analysis for scientific data visualization
Leila De Floriani
University of Maryland Institute for Advanced Computer Studies, University of Maryland
The visualization of currently available scientific datasets (describing terrains, 3D scalar or vector fields, etc.), usually of very large size, requires effective spatial data structures for efficiently encoding such data sets as well as powerful and compact topological descriptors. Data representation and topology-based visualization are two fundamental lines of the current research in scientific data visualization. The first part of the talk will focus on two recent contributions of our research on efficient spatial data structures for representing scalar fields: Sparse Pyramids, compact multi-resolution representations for terrains and volume datasets, and the Stellar Tree, a compact spatio-topological data structure for irregularly distributed data, naturally geared to a parallel and distributed computation. The second part of the talk will discuss topology-based techniques for data visualization, and, specifically, morphological segmentations based on discrete Morse theory, called Morse-Smale complexes. A discrete gradient field is computed from the scalar field values, and simplified in order to eliminate critical points that arise on account of noise, or that correspond to uninteresting morphological features. Algorithms for building and simplifying a discrete Morse gradient, and for computing a Morse-Smale complex are presented. Applications of such topological descriptors will also be discussed.
(This is joint work with Federico Iuricich, Riccardo Fellegara, Paola Magillo, Kenneth Weiss)