Title page for ETD etd-4437152139711101


Type of Document Dissertation
Author Zabaronick, Noel A.
URN etd-4437152139711101
Title Eye Tracking Using Fiber Optics and Computer Vision Techniques
Degree Master of Science
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Claus, Richard O. Committee Chair
Abbott, A. Lynn Committee Member
de Vries, Marten Committee Member
Wang, Anbo Committee Member
Keywords
  • none
Date of Defense 1997-04-04
Availability unrestricted
Abstract
We describe a system for tracking the motion and

determining the velocity of the human eye using a

combination of fiber optics and imaging optics integrated

with a CCD camera, a framegrabber, and a PC. Systems

such as the one we describe are needed for monitoring

location of interest for better human- computer

interfaces and virtual reality simulations, for monitoring

pilot cognitive skills during flight simulations, and for

detecting the early warning signs of driver drowsiness.

Where some eye-tracking devices are cumbersome

because they require a person to limit head motion to

remain in view of a camera or uncomfortable because

they require the use of an elaborate headpiece, our

proposed system is as simple to wear as a pair of

eyeglasses, with the only added weight to the glasses

being that of a fiber optic bundle.

This fiber bundle guides the image of an 880 nm LED

illuminated eye as it is reflected from a hot mirror built

into the eyeglass assembly. The guided image is focused

onto a CCD and the camera's output is linked to a PC

framegrabber card. Software written in Microsoft Visual

C++ locates the user's pupil in each video image and

tracks the motion and velocity of the pupil over time.

The prototype system tracks the center of the pupil to an

accuracy of only 1/5 of the pupil size. This diminished

accuracy results from the minimized computation scheme

of pupil detection. The technique relies on edge detection

and direction of image gradient over very few pixels so

that the system is optimized for speed. Many other

methods of pupil detection could be investigated in future

research in order to optimize such a system for other

parameters.

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