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Talks & Seminars
Topological Analysis for Scientific Visualization
Vijay Natrajan, UC Davis
Date & Time: January 19, 2006 14:15
Venue: Kresit SIC 205
Abstract:
Scientific datasets are becoming increasingly complex making it difficult to analyze them visually. Automatic detection of features in the data help the user to first identify regions of interest and then study them individually. We perform topological analysis based on ideas from Morse theory in order to detect features in scalar data. Morse theory relates critical points of a function to the topological shape of its domain space. We characterize critical points of piecewise linear functions and partition the domain into crystal shaped cells, each of which is defined by a pair of critical points. This partition, called the Morse-Smale complex, is used to explore features in the data that span multiple scales. In this talk, I will sketch an algorithm to construct the Morse-Smale complex and present two atomic operations that simplify the complex thereby removing small-scale features. I will demonstrate the usefulness of our approach by presenting several applications.
Speaker Profile:
Vijay Natarajan is a postdoctoral researcher in the Institute for Data Analysis and Visualization at University of California, Davis. His research interests include scientific visualization, computational geometry, computational topology, computer graphics, and meshing. Vijay received a Ph.D. in computer science from Duke University in 2004. He holds M.Sc. and B.E. degrees in mathematics and computer science, respectively, from Birla Institute of Technology and Science, Pilani.
http://graphics.idav.ucdavis.edu/~vijayn/resume/cv.pdf
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