Drowsiness is a major cause of accidents, in particular in road transportation. It is thus crucial to develop robust drowsiness monitoring systems. There is a widespread agreement that the best way to monitor drowsiness is by closely monitoring symptoms of drowsiness that are directly linked to the physiology of an operator such as a driver. The best systems are completely transparent to the operator until the moment he/she must react. In transportation, cameras placed in the passenger compartment and looking at least at the face of the driver are most likely the best way to sense physiology related symptoms such as facial expressions and the fine behavior of the eyeballs and eyelids. We present here the new database1 called DROZY that provides multiple modalities of data to tackle the design of drowsiness monitoring systems and related experiments. We also present two novel systems developed using this database that can make predictions about the speed of reaction of an operator by using near-infrared intensity and range images of his/her face.
['Quentin Massoz', 'Thomas Langohr', 'Clémentine François', 'Jacques Verly']
The ULg multimodality drowsiness database (called DROZY) and examples of use