Peripheral visual field danger identification method based on human vision and machine vision coupling

Abstract

The invention discloses a peripheral visual field danger identification method based on human vision and machine vision coupling. The method is characterized by firstly, according to an eye tracker experiment, acquiring driver eye moving data, and extracting a coordinate point area reflecting that a driver visual line type is stare; then, carrying out three standard area division based on human eye imaging principle on a camera image, comparing a driver stare point area with standard division areas, and removing the standard division area where the stare point area belongs; and finally, processing the two remaining standard division areas according to a priority, and identifying whether an object is moving and determining whether the object is dangerous to a vehicle. A multi-target dangeridentification problem in the front visual field of a driver is solved, an image identification range is reduced; and priority processing is performed on the peripheral visual field area, the monitoring of a key area is reinforced, and real time image processing efficiency is increased.

Description

Technical field [0001] The present invention relates to the technical field of driver assistance safety and automobile active safety, in particular to a processing method for the peripheral field of vision in front of a vehicle. Background technique [0002] Road traffic is a crisscross and intricate system. Only when the three major parts of the system are coordinated and coordinated with each other can they operate effectively. Motor vehicle drivers are the information hub of the human-vehicle-road system. All traffic accidents caused by human-related factors account for more than 90% of the total. Drivers get the most information through their eyes, and the proportion is actually as high as 80%. People can only selectively process the information in the visual field, which is called visual selective attention. In a natural driving state, motor vehicle drivers have different attention mechanisms to stimuli located in the central field of vision and peripheral field of vision,...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problem of peripheral vision hazard identification in the driver's driving process in the prior art, the present invention provides a peripheral vision hazard identification method based on the coupling of human vision and machine vision

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