Date of Award

2022

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

Committee Chair

Haeyong Chung

Committee Member

Timothy Newman

Committee Member

Jacob Hauenstein

Subject(s)

Information visualization, Optical data processing, Augmented reality

Abstract

Visual data analysis and sensemaking can benefit from utilizing multiple displays to organize large amounts of information. However, analyzing information scattered across multiple displays can be challenging. Existing solutions to solving this problem often require mental effort to understand cross-display relationships. A hybrid approach, named AR-SAViL, is presented which addresses this problem by using an augmented reality headset to track displays and their contents in real time, drawing visual links directly between related information. The performance of the system is evaluated through exploration of an existing dataset and expert review, and findings suggest AR-SAViL has potential to assist visual analysis and sensemaking when using multiple displays.

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