Blinking frequency and sight line estimation method based on eye region generation network

Abstract

The invention discloses a blinking frequency and sight line estimation method based on an eye region generation network. The method can be used for carrying out early warning on fatigue driving of a driver. Particularly, the method comprises the steps of: firstly, applying machine deep learning to extract an eye feature region of the driver, which is shot by a camera; carrying out driver eye simulation on the feature region by an ellipse fitting method; and determining a blinking frequency and pupil positions by combining perclos. The estimation method gives out the blinking frequency and a sight line direction of the driver and provides supporting bases for a driver fatigue monitoring system and driver dynamic behavior analysis.

Description

technical field

[0001] The invention belongs to the field of automobile safety and relates to a method for estimating the driver's blinking frequency and line of sight, and the method can be used for early warning of driver's fatigue driving. Background technique

[0002] At present, traffic accidents caused by fatigue driving still occupy the main component. Therefore, the successful early warning of drivers under driving fatigue has become a problem that people pay more and more attention to. This has also led most researchers to propose many effective auxiliary measures for this problem. The development of image processing technology and the extraction of facial features have provided a theoretical basis for the research on driver fatigue warning methods, but they are still immature. period. E.g:

[0003] Since the target may appear anywhere in the image, and the size and aspect ratio of the target are also uncertain. In the process of traditional target detection, the...

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