Vision based AI for drowsiness detection – a high risk approach to a solved problem
Vision-based AI is a dangerous approach for drowsiness detection. This presentation covers several risks and pitfalls automotive suppliers will encounter. These stem from misconceptions and incorrect assumptions about the nature of drowsiness. We present an alternative approach that is based on a physiological biomarker for drowsiness using eyelid movements. This methodology can easily be incorporated into all vision-based driver monitoring systems, today. In addition, we will discuss other neurological biomarkers that can be derived from eyelid movement, such as onset of Alzheimer’s, epilepsy and neurotoxicity.