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Robust eyelid tracking for fatigue detection | IEEE Conference Publication | IEEE Xplore

Robust eyelid tracking for fatigue detection


Abstract:

We develop a non-intrusive system for monitoring fatigue by tracking eyelids with a single web camera. Tracking slow eyelid closures is one of the most reliable ways to m...Show More

Abstract:

We develop a non-intrusive system for monitoring fatigue by tracking eyelids with a single web camera. Tracking slow eyelid closures is one of the most reliable ways to monitor fatigue during critical performance tasks. The challenges come from arbitrary head movement, occlusion, reflection of glasses, motion blurs, etc. We model the shape of eyes using a pair of parameterized parabolic curves, and fit the model in each frame to maximize the total likelihood of the eye regions. Our system is able to track face movement and fit eyelids reliably in real time. We test our system with videos captured from both alert and drowsy subjects. The experiment results prove the effectiveness of our system.
Date of Conference: 30 September 2012 - 03 October 2012
Date Added to IEEE Xplore: 21 February 2013
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Conference Location: Orlando, FL, USA

References

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