Publication | Open Access
Presenting a model for dynamic facial expression changes in detecting drivers' drowsiness.
18
Citations
3
References
2015
Year
EngineeringFeature DetectionBiometricsAdvanced Driver-assistance SystemPsychologySocial SciencesFace DetectionFacial Recognition SystemImage AnalysisDriver BehaviorPattern RecognitionAffective ComputingCompound ModelVision SensorSleepCognitive ScienceBehavioral SciencesMachine VisionDrowsiness Detection SensorsComputer ScienceWeak PointsDriver PerformanceComputer VisionFacial Expression RecognitionEye TrackingEmotionEmotion Recognition
Drowsiness while driving is a major cause of accidents. A driver fatigue detection system that is designed to sound an alarm, when appropriate, can prevent many accidents that sometime leads to the loss of life and property. In this paper, we classify drowsiness detection sensors and their strong and weak points. A compound model is proposed that uses image processing techniques to study the dynamic changes of the face to recognize drowsiness during driving.
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