EYE RECOGNITION SYSTEM TO PREVENT ACCIDENTS ON THE ROAD
- Financial University under the Government of the Russian Federation, 125993 Leningradskiy pr-t, h. 49, Moscow, Russia
Keywords: Face Detection, Face Recognition, Eye Detection, Eye Recognition, Convolutional Neural Networks, Haar Detector, Recall, Skip Target
Abstract. Today, possibilities of artificial intelligence allow us to see the emergence of autonomous cars. However, there are still many problems in this area at present. Often, such vehicles are “too slow to think”, are not able to reliably process data from video cameras in the event of reflections, glare, and there are also questions about the safety of such driving in difficult weather conditions or in heavy traffic. At the same time, the human factor plays a major role in accidents of driven vehicles. Many accidents involve driver fatigue, distraction, or even falling asleep. At the same time, it is potentially possible to monitor the state of a person behind the wheel by a video sequence received from a camera installed in the car's interior and registering the driver's face in video sequence. In this paper, the existing databases of images of faces and eyes are considered, and an algorithm is presented that detects the state of closed eyes based on Haar detectors and convolutional neural networks.