Communication via Eye Blinks
Detection and Duration
Analysis in Real Time
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Kristen Grauman |
Margrit Betke |
James Gips |
Gary Bradski |
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Vision Interface Group |
Image and Video Computing |
EagleEyes |
Visual Interactivity Group |
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MIT |
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Intel Corporation |
Abstract
A method for a real-time vision system that
automatically detects a user's blinks and accurately measures their durations
is introduced. The system is intended to provide an alternate input
modality to allow people with severe disabilities to access a computer.
Voluntary long blinks trigger mouse clicks, while involuntary short blinks are
ignored. The system enables communication using "blink
patterns:" sequences of long and short blinks which are interpreted as
semiotic messages. The location of the eyes is determined automatically
through the motion of the user's initial blinks. Subsequently, the eye is
tracked by correlation across time, and appearance changes are automatically
analyzed in order to classify the eye as either open or closed at each
frame. No manual initialization, special lighting, or prior face
detection is required. The system has been tested with interactive games
and a spelling program. Results demonstrate overall detection accuracy of
95.6% and an average rate of 28 frames per second.
The following are short sample outputs of
the system described in this work. A red dot appearing over the eye
denotes that a short blink was detected, while a blue dot denotes that a long
blink was detected. The initial blue rectangles surrounding the eyes and
face indicate the results of the motion analysis phase. The following light
blue rectangle around one eye indicates the tracker's search space, and the
inner purple rectangle represents the best match for the open eye template.
Demo
1 : Shows long / short blinks and reinitialization of tracker
Demo
2 : Shows user with glasses
Demo
3 : Includes some quick head motion