19-09-2017, 01:13 PM
Vehicle accidents are more common if driving is inadequate. These happen on most factors if the driver is drowsy or if he is an alcoholic. Drowsiness of the driver is recognized as an important factor in vehicle accidents. It was shown that driving performance deteriorates with increased drowsiness with resulting accidents that constitute more than 20% of all vehicle accidents. But life once lost can not be re-winded. Advanced technology offers some hope of avoiding these to a certain extent.
It uses cameras of load-coupled devices remotely equipped with active infrared illuminators to acquire images of video of the controller. Several visual cues that typically characterize a person's alert level are extracted in real time and are systematically combined to infer the level of driver fatigue. The visual cues used characterize the movement of the eyelid, the movement of the gaze, the movement of the head and the facial expression. A probabilistic model is developed to model human fatigue and predict fatigue based on the visual signals obtained. The simultaneous use of multiple visual signals and their systematic combination produces a much more robust and accurate characterization of fatigue than the use of a single visual signal. This system was validated under conditions of real-life fatigue with human subjects of different ethnic origins, genres and ages; with / without glasses; and under different lighting conditions. It was found to be reasonably robust, reliable and accurate in characterizing fatigue.
It can be understood in the following video: