Iris and Pupil Measurement on Low Resolution Images for Driver Observation

Given the fact that the eyes are one of the most important clues for the driver’s attention in cases of traffic accidents, we propose a robust method for accurate iris and pupil detection and parameter estimation. The latter can be used to infer the eye gaze. The presented video-based system is calibration-free and does not require any training procedure. We implemented and adapted an eye feature extraction technique using computer-vision methods and estimated pupil and iris parameters with the help of a polar representation of the eye image. In order to detect the glints (reflections on the eye cornea), caused by the infrared illumination mounted on the camera, we apply a corner detection algorithm. The experiment results show high applicability of the presented eye feature extraction on low resolution images.