Method for establishing urban road vehicle image database

Abstract

The invention discloses a method for establishing an urban road vehicle image database, which mainly solves the problem that the existing vehicle database is not complete and cannot effectively describe an urban traffic condition. By adopting an implementation scheme, the method comprises the following steps: determining a data acquisition scheme and acquiring an original video of a road vehicle according to factors of vehicle types, different scenes, photographing angle, illumination variation and weather condition; converting the original video into an image, and defining an interested area in the image by utilizing a trapezoidal frame; performing fuzzy processing on the non-interested area outside the trapezoidal frame; marking a vehicle image in the interested area, and generating a txt-format tag file; and converting the txt-format tag file to a corresponding xml-format tag file to be stored, and acquiring the vehicle database. By adopting the method, information about a vehicle position and type can be accurately given, reliable data support can be provided for training a deep convolutional neural network, and the method can be used for an intelligent traffic system.

Description

technical field [0001] The invention belongs to the technical field of image recognition, and in particular relates to a method for constructing an image database of urban road vehicles, which can be used for deep convolutional neural network training in intelligent transportation systems. Background technique [0002] my country's urban road traffic management is facing a rather severe situation. In recent years, with the rapid development of social economy and the rapid promotion of urbanization, various means of transportation have been increasing, showing a trend of diversified and rapid growth. The existing road resources are gradually becoming saturated, which not only restricts social and economic development, but also brings a series of traffic accidents, such as traffic jams and car accidents, which seriously affect the public's traffic travel. Therefore, it is urgent to improve the traffic management method, improve the management level, and alleviate the existing...

AI Technical Summary

Problems solved by technology

At present, there are some vehicle image databases at home and abroad, such as the KITTI database released by the German Karlsruhe Institute of Technology team in 2013, and the database shot on the Suzhou Expressway established by the Chinese Academy of Sciences in 2012, but these databases are all for specific problems. However, the coverage of vehicle categories, road conditions, weather conditions, and shooting angles are insufficient, and cannot effectively describe urban traffic in China, which can easily lead to overfitting of the built model, robustness of detection and classification, and generalization lack of ability

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