Real-time eye detection and tracking in the near-infrared video for drivers’ drowsiness control

Abstract

This paper presents a visual system for real-time eye detection and tracking in the near-infrared (NIR) video streams for drivers’ monitoring. The system starts with crude eye position estimation based on an eye model suitable for NIR processing. In the next step, eye regions are verified with the classifier operating in the higher-order decomposition of the tensor of eye prototypes. Finally, the process is augmented with the linear tracker which facilitates eye detection and allows real-time operation necessary in the automotive environment. The reported experiments show high accuracy and real-time operation of the system in the car.