From face images to a level of drowsiness
Quentin Massoz will publicly defend his doctoral thesis entitled "Non-invasive, automatic, and real-time characterization of drowsiness based on eye closure dynamics »
Drowsiness is a complex physiological state associated with a difficulty of staying awake, a strong inclination towards falling asleep. When performing a task, drowsiness impairs the ability of an individual to make sound decisions and to complete said task at adequate performance. When the task is critical, drowsiness therefore becomes a danger that puts human lives at risk. In facts, drowsiness is a major cause of fatal accidents, in particular in the transportation sector where it is estimated to be responsible for 20–30% of them. There is thus a clear need for automatic, real-time drowsiness characterization systems that aim at preventing such accidents by issuing timely drowsiness warnings to vehicle operators.
This thesis is about drowsiness characterization systems that operate non-invasively, automatically, and in real-time from a video stream of face images, with a focus on the analysis of eye closure dynamics. In addition to providing a comprehensive discussion about the development of such systems, we present three novel systems: a baseline system, a multi-timescale system, and a parametric system. We thoroughly evaluate the performance of our machine-learning-based systems, and provide key insights on how they operate/make their decisions.
Promotor : Marc Van Droogenbroeck
The defence (in english) is open to all and will take place on Wednesday, April 24, 2019 at 9:00 am, in room R7 of the Montefiore Institute, Building B28, at Sart Tilman (access)