Date of Award

Summer 2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

Committee Director

Sampath Jayarathna

Committee Member

Michele C. Weigle

Committee Member

Michael L. Nelson

Committee Member

Vikas G. Ashok

Committee Member

Anne M. Perrotti

Abstract

Eye-tracking offers insights into human cognition and attention allocation by capturing and interpreting eye movements. Traditionally, eye tracking research has relied on offline analysis methods, requiring post-experiment processing to derive insights from gaze data. This approach limits its applicability in contexts requiring immediate feedback and adaptive responses based on real-time gaze behaviors. Recent advancements in computing power and eye tracking technology have enabled a shift towards real-time analysis, allowing modern systems to interpret gaze data with minimal latency, facilitating integration into interactive applications and experiments. Despite these advancements, existing tools often face challenges with real-time computation of advanced gaze measures due to the computational complexity involved. Algorithms typically used to derive these measures often require processing entire datasets, which can constrain their applicability in real-time settings.

To address these challenges, we introduce RAEMAP (Real-Time Advanced Eye Movements Analysis Pipeline), a novel software designed for real-time eye tracking analysis. RAEMAP features algorithms that enable real-time computation of both basic and advanced gaze measures, including real-time pupil dilation-based cognitive assessment, dynamic indicators of visual search behavior, and predictive analysis of gaze transitions. RAEMAP bridges the gap between traditional offline methods and the need for real-time insights by providing an immediate understanding of complex visual and cognitive processes.

Rights

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

DOI

10.25777/9rrm-3592

ISBN

9798384456766

ORCID

0000-0002-9523-3346

Available for download on Tuesday, September 30, 2025

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