Fundamentals of digital image processing
Fundamentals of digital image processing
Active Facial Tracking for Fatigue Detection
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Driver Fatigue Detection Based Intelligent Vehicle Control
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Driver Hypo-vigilance Detection Based on Eyelid Behavior
ICAPR '09 Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition
Detecting driver drowsiness using feature-level fusion and user-specific classification
Expert Systems with Applications: An International Journal
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Assessing a driver's state of awarness and fatigue is especially important to reduce the number of traffic accidents often involving bus and truck drivers, who must work during several hours under monotonous road conditions. Two main challenges arise in resolving the state of alert: first, the system must be capable of detecting the driver's face location; secondly, the driver's facial cues, such as blinking, yawning, and eyebrow rising must be recognized. Our approach combines the well-known Viola-Jones face detector with motion analysis of Shi-Tomasi salient features within the face to determine the driver's state of alert. The location of the eyes and blinking are cues whose detection is also important. To this end, the proposed method takes advantage of the high reflectivity of the retina to near infrared illumination employing a camera with an 850 nm wavelength filter. Motion analysis of the salient points, in particular cluster mass centers and spatial distribution, has proved successful in determining the driver's state of alert.