Weak supervision video license plate recognition method based on point labeling information of eye tracker

Abstract

The invention belongs to the technical field of license plate detection, and relates to a weak supervision video license plate recognition method based on point labeling information of an eye tracker, which comprises the following steps of: generating a viewpoint position coordinate through the eye tracker, generating viewpoint region information from the coordinate position of the eye tracker by adopting a viewpoint smoothing mode, generating a large number of peripheral bounding box recommendations through a selective search algorithm, and carrying out point labeling on the peripheral bounding box recommendations. The consistency between the viewpoint area and the peripheral bounding box is calculated to determine an initial peripheral bounding box, and the quality of the initial peripheral bounding box is improved through inter-frame consistency; then, based on the viewpoint area information, a high-quality license plate peripheral bounding box is generated by adopting an area generation algorithm, the generated peripheral bounding box is used for training a test network, and a license plate detection result is generated by using the test network, so that the problems of inclination and distortion of the license plate are solved, and weak supervision video license plate detection based on the viewpoint area can be realized; and the method can also be used for various inclined target detection tasks such as scene text detection and supermarket commodity detection.

Description

technical field [0001] The invention belongs to the technical field of license plate detection, and relates to a weakly supervised video license plate recognition method based on eye tracker point annotation information. Background technique [0002] After entering the era of big data, artificial intelligence technology is of great significance for the construction of smart cities. As an important part of smart transportation, license plate recognition has strong practical significance and application value. It is used to solve the monitoring of illegal vehicles in traffic management; it is difficult to park in residential areas, shopping malls, scenic spots and other places. With the rapid development of machine learning technology, deep learning technology has become the mainstream in the field of license plate recognition. Compared with the traditional license plate recognition system, the neural network model constructed by deep learning technology using datasets has dem...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art, design and provide a weakly supervised video license plate recognition method based on eye tracker point labeling information, and build a video license plate detection data set based on eye tracker point labeling information to solve the problem. The current video license plate recognition data set is complex and the generalization ability of the model recognition algorithm is poor, so as to facilitate the video license plate recognition of large-scale scenes

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