Method for rapidly detecting facial features of driver based on Haar-like features

Abstract

A method for rapidly detecting facial features of a driver based on Haar-like features comprises the steps that in the first stage, a current image patch is detected through a classifier and the level of similarity of the content of the image patch and a target is estimated according to a detection result; in the second stage, according to the detection result, the similarity of a detection result of the next time is estimated with the combination of an algorithm, and the step size of searching and the detection accuracy of the classifier are adjusted according to the estimated result; in the third stage, combined with a driving scene of the driver and according to detected position information of an area containing the target, the accurate position of the target is estimated. The mode that the detection accuracy of the classifier is dynamically adjusted is adopted, under the condition that the accuracy is not reduced, the number of times of repeated calls of the classifier is reduced, detection time is shortened, and the detection efficiency is improved.

Description

technical field [0001] The invention relates to a fast detection method of driver's facial features based on Haar-like features, which belongs to the fields of intelligent transportation, pattern recognition and embedded systems. Background technique [0002] With the growth of my country's economy, the number of locomotives owned by residents in my country has increased rapidly. While greatly facilitating people's travel, the incidence of road traffic accidents is also rising, causing huge losses to people's lives and property and the national economy. From the perspective of the causes of road traffic accidents, drivers are the main factor leading to traffic accidents, while pedestrians are the main victim groups in traffic accidents. According to statistics, in 2013, the number of pedestrians who died due to traffic accidents in my country was about 27,906, accounting for 29.81% of all traffic accident deaths; the number of pedestrians injured due to traffic accidents wa...

AI Technical Summary

Problems solved by technology

Its disadvantage is that the detection accuracy of the classifier cannot be adjusted according to the image content, that is, the classifier is always called from the first layer

Therefore, a large number of repeated calculations are performed in the detection process, and the efficiency is low.

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