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Summary: USING INFRARED ILLUMINATION TO IMPROVE EYE & FACE TRACKING IN LOW
QUALITY VIDEO IMAGES
R. Youmaran and A. Adler
Carleton University, Ottawa, Ontario
adler@sce.carleton.ca
ABSTRACT
We propose a novel eye and face tracking algorithm using
active infrared (IR) illumination. Most eye trackers based on
active IR illumination require bright pupil images to
successfully detect eyes in image sequences. However, due
to factors such as eye closure, head rotation, variation in
illumination and occlusion, most trackers tend to fail in
these situations where pupil shows weak reflections. Our
proposed method overcomes these limitations by making
use of the dark-bright pupil difference images as well as
using adaptive thresholding techniques. The core
computational module of the algorithm is based on the
Kalman filter and adaptive template matching to find and
update the most probable eye position in the current frame.
Our eye tracker can robustly detect faces and track eyes in a
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