Introduction - If you have any usage issues, please Google them yourself
Driver fatigue is one of the leading causes of traffic accidents.
Therefore, the use of assistive systems that monitor a driver’s
level of vigilance and alert the driver in case of drowsiness
and distraction can be significant in the prevention of
accidents. This paper presents morphology based operations
in extracting various visual cues like eye, eye brows, mouth
and head movement. The parameters used for detecting
fatigue are: eye closure duration measured through eye state
information, head movement through orientation of head
ellipse and yawning analyzed through mouth state
information. This system was validated with synthetic data
under real-life fatigue conditions with human subjects of
different ethnic backgrounds, genders, and ages and under
different illumination conditions. It was found to be
reasonably robust, reliable, and accurate in fatigue
characterization