High Accuracy Eye-Tracker For Proton Clinic Environment

Master thesis (2019)

Authors

Y. Zhang Electrical Engineering, Mathematics and Computer Science

Contributors

M.H.G. Verhaegen Team Raf Van de Plas - Mechanical, Maritime and Materials Engineering (mentor)
O.A. Soloviev Team Raf Van de Plas - Mechanical, Maritime and Materials Engineering (graduation committee member)
A.J. van Genderen Computer Engineering - EEMCS (coach)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2019 Yu Zhang
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Published Date

29-10-2019

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

This project aims to improve the accuracy of the eye tracking system, which consists of two cameras and two infrared LED light sources. This highly non-invasive technology, which is the feature-based video-oculographic eye tracking system, determines the position of the eye by monitoring the eye features such as the pupil center and glints. The accuracy of estimating the eye position and orientation is critical in the proton clinic environment, and is to be required higher than those in commercially available eye-tracking system.

Files

MscThesis_Yu.pdf
(.pdf | 4.32 Mb)