Abstract
Non-intrusive methods based on active remote IR illumination for eye tracking are important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. Based on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.
Highlights
Automobile and truck drivers have various emotions, such as fatigue, stress, and distraction
Driver fatigue is closely related to brain activity, eye movement, degree of mouth openness, heart rate, body posture, skin conductance, and so on
Drivers in fatigue exhibit certain visual cues such as eye movement, head movement, mouth opening and closing, and facial expressions that are observed from an image
Summary
Automobile and truck drivers have various emotions, such as fatigue, stress, and distraction. The key to resolve the problem is to developing a system in which can recognize driver fatigue Around this idea, many studies have been done in both the visual field and non-visual field. Driver fatigue is closely related to brain activity, eye movement, degree of mouth openness, heart rate, body posture, skin conductance, and so on. Drivers in fatigue exhibit certain visual cues such as eye movement, head movement, mouth opening and closing, and facial expressions that are observed from an image. In this direction, much progress has been achieved.
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