16 mars 2017

A Driver Face Monitoring System for Fatigue and Distraction Detection

A Driver Face Monitoring System for Fatigue and Distraction Detection Driver face monitoring system is a real-time system that can detect driver fatigue and distraction using machine vision approaches. In this paper, a new approach is introduced for driver hypovigilance (fatigue and distraction) detection based on the symptoms related to face and eye regions. In this method, face template matching and horizontal projection of top-half segment of face image are used to extract hypovigilance symptoms from face and eye, respectively.... [Lire la suite]

22 février 2017

Detecting hypovigilance, fatigue, and distraction with the NEXYAD real time driving risk assessment SafetyNex

Detecting hypovigilance, fatigue, and distraction with the NEXYAD real time driving risk assessment SafetyNex SafetyNex estimates driving risk in real time. The approach is to estimate if the driving behaviour (speed and acceleration) are appropriate or inappropriate to the infrastructure difficulty : on a disused airport, high speed and aggressive behaviour is not dangerous, although it is in front on a school, or approaching a narrow curve, etc ... read more :... [Lire la suite]
08 février 2017

SafetyNex driving risk profiles may solve the problem of hypovigilance and fatigue detection

SafetyNex driving risk profiles may solve the problem of hypovigilance and fatigue detection SafetyNex is a nomadic real-time risk estimation system, based on Artificial Intelligence (AI). The system has been described in detail in previous publications and uses the key concept of "near-accident" or "quasi-accident", and is a result of 15 years of collaborative research with road safety experts and researchers. See http://www.safetynex.net The main competitive advantage of SafetyNex is that it allows, since the risk is... [Lire la suite]
18 novembre 2014

Fatigue sensor: When EPFL innovates

Fatigue and drowsy driving are often the cause of accidents of traffic. Several drowsiness detection systems already been tested in practice. EPFL innovates in this area: a student recently proposed a fatigue detection algorithm based on video the analysis of eye closure. A prototype will be tested in terms actual driving. La fatigue et la somnolence au volant sont bien souvent à l’origine d’accidents de la circulation. Plusieurs systèmes de détection de la somnolence ont déjà été testés dans la pratique. L’EPFL innove dans ce... [Lire la suite]