Gaussian background modeling and recurrent neural network combined vehicle type classification method

Abstract

Provided is a Gaussian background modeling and recurrent neural network combined vehicle type classification method. A Gaussian mixture model is used to extract a moving object, the moving object is sent to the recurrent neural network for feature extraction, and whether the moving object is a vehicle as well as the vehicle type are determined according to a vector output by the recurrent neural network (RNN). According to the invention, RNN is used for subsequent operation of the Gaussian mixture model to achieve the goal of vehicle type classification, the Gaussian mixture model is used to carry out background modeling on a video sequence, a moving object area is detected, CNN is used to classify the detected moving object area, and classification results are input the RNN to obtain final classification and further determine whether the object is a carriage or a lorry or is not a vehicle. Gaussian background modeling is combined with the recurrent neural network creatively, the method is highly robust, and the vehicle detecting and vehicle type identifying precision can be improved greatly.

Description

technical field [0001] The invention relates to computer vision classification technology, in particular to a method for realizing vehicle classification by using Gaussian background modeling combined with a cyclic neural network. Background technique [0002] With the rapid development of society and economy, Intelligent Transportation System (ITS) plays an increasingly important role in traffic management. Traffic parameters such as traffic volume and average speed collected by the ITS system can provide a reliable basis for the analysis and management of the traffic management department. The traditional vehicle detection method is to use induction coils to collect traffic parameters. This method is easy to damage the road surface and is troublesome to install and maintain. The vision-based video detection technology can not only collect traffic parameters, but also classify vehicle types. Moreover, the vehicle detection technology of surveillance video is one of the im...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is: the existing technology cannot overcome the false detection caused by the Gaussian mixture model under the change of illumination and the shaking of branches, and the recognition accuracy needs to be improved

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