Browsing by Author "Sridharamurthy, Raghavendra"

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    Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization
    (The Eurographics Association and John Wiley & Sons Ltd., 2021) Yan, Lin; Masood, Talha Bin; Sridharamurthy, Raghavendra; Rasheed, Farhan; Natarajan, Vijay; Hotz, Ingrid; Wang, Bei; Smit, Noeska and Vrotsou, Katerina and Wang, Bei
    In topological data analysis and visualization, topological descriptors such as persistence diagrams, merge trees, contour trees, Reeb graphs, and Morse-Smale complexes play an essential role in capturing the shape of scalar field data. We present a state-of-the-art report on scalar field comparison using topological descriptors. We provide a taxonomy of existing approaches based on visualization tasks associated with three categories of data: single fields, time-varying fields, and ensembles. These tasks include symmetry detection, periodicity detection, key event/feature detection, feature tracking, clustering, and structure statistics. Our main contributions include the formulation of a set of desirable mathematical and computational properties of comparative measures, and the classification of visualization tasks and applications that are enabled by these measures.
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    Time‐varying Extremum Graphs
    (© 2024 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2024) Das, Somenath; Sridharamurthy, Raghavendra; Natarajan, Vijay; Alliez, Pierre; Wimmer, Michael
    We introduce time‐varying extremum graph (), a topological structure to support visualization and analysis of a time‐varying scalar field. The extremum graph is a sub‐structure of the Morse–Smale complex. It captures the adjacency relationship between cells in the Morse decomposition of a scalar field. We define the  as a time‐varying extension of the extremum graph and demonstrate how it captures salient feature tracks within a dynamic scalar field. We formulate the construction of the  as an optimization problem and describe an algorithm for computing the graph. We also demonstrate the capabilities of  towards identification and exploration of topological events such as deletion, generation, split and merge within a dynamic scalar field via comprehensive case studies including a viscous fingers and a 3D von Kármán vortex street dataset.