Publication Date

10-10-2013

Type of Culminating Activity

Thesis

Degree Title

Master of Science in Computer Science

Department

Computer Science

Major Advisor

Alark Joshi

Advisor

Kristin Potter

Advisor

Amit Jain

Abstract

With data sets growing in size, more efficient methods of visualizing and analyzing data are required. A user can become overwhelmed if too much data is displayed at once and be distracted from identifying potentially important features. This thesis presents methods for focus+context visualization of vector fields. Users can interact with the data in real time to choose which regions should have more emphasis through a mouse or touch interface. Streamlines and hedgehog based visualizations are used to provide focus+context to vector visualizations. The presented visualization methods are shown to be more computationally efficient and are shown to scale well to smaller resource platforms (such as tablets), while user evaluations indicate user performance for feature analysis and particle advection was similar to existing techniques.

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