Title page for ETD etd-0907104-084847

Document Type	thesis
Author Name	Patro, Anilkumar G
URN	etd-0907104-084847
Title	Pixel Oriented Visualization in XmdvTool
Degree	MS
Department	Computer Science
Advisors	Prof. Matthew O. Ward, Advisor Prof. Emmanuel Agu, Reader Prof. Michael Gennert, Department Head
Keywords	visualizing large data sets exploratory multivariate visualization
Date of Presentation/Defense	2004-09-02
Availability	unrestricted
Abstract Many approaches to the visualization of multivariate data have been proposed to date. Pixel oriented techniques map each attribute value of the data to a single colored pixel, theoretically yielding the display of the maximum possible information at a time. A large number of pixel layout methods have been proposed, each of which enables users to perform their visual exploration tasks to varying degrees. Pixel oriented techniques typically maintain the global view of large amounts of data while still preserving the perception of small regions of interest, which makes them particularly interesting for visualizing very large multidimensional data sets. Pixel based methods also provide feedback on the given query by presenting not only the data items fulfilling the query but also the data that approximately fulfill the query. The goal of this thesis was to extend XmdvTool, a public domain multivariate data visualization package, to incorporate pixel based techniques and to explore their strengths and weaknesses. The main challenge here was to seamlessly apply the interaction and distortion techniques used in other visualization methods within XmdvTool to pixel based methods and investigate the capabilities made possible by fusing the various multivariate visualization techniques.
Files	patro.pdf

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