A fatigue detection device to help keep your eyes on the road
July 17, 2013
An EPFL student, Peugeot Citroën, has developed a video analysis algorithm able to estimate the level of a driver’s fatigue based on the degree of eyelid closure and has built a prototype to test it in real driving conditions.
Nearly a third of highway accidents are caused by fatigue. Nowadays, there exist several attention detection systems for drivers, such as detection of loss of vehicle control.
Marina Zimmermann, as part of her master thesis in electrical and electronic engineering and in partnership with Citroën, has focused directly on drivers and their state of wakefulness. She developed an algorithm able to measure the degree of eyelid closure by using a single camera and thus avoiding invasive methods.
One of the indicators most frequently used to determine the state of a driver’s fatigue is “PERCLOS” (percentage of eye closure). It measures the percentage of time that the pupil is at least 80% covered by the eyelid during a predetermined time span. The challenge was to measure this indicator in real time, keeping the drivers’ eyes on the viewfinder and bearing in mind that they can turn their head, wear glasses, drive during the night, cross through tunnels etc.
The Signal Processing Laboratory 5 (LTS5) at EPFL placed a small infrared camera behind the wheel, and Zimmermann created an algorithm to disregard possible light effects as well as the drivers’ different eye morphologies. She then established a 3D profiling of the eye and eyelids so as to distinguish an open from a closed eye.
The first tests carried out under real conditions showed good reliability and the algorithm can run on a standard camera. It will be able to combine other data provided by an an existing face tracking system, like yawning or head tilt.