Traffic illegal detection method based on vehicle tracking and system

Abstract

The invention relates to the technical field of the traffic illegal detection and in particular to a traffic illegal detection method based on vehicle tracking and a system. The method comprises the following steps: pre-building a vehicle 3D model according to monitoring video data of an actual road; and in the process of actual detection, marking and tracking the vehicle by using the vehicle 3D model, judging whether the vehicle has the traffic illegal act according to the video image data generated by the tracked vehicle. The method is capable of marking the vehicle by using the vehicle 3D model, and using the tracking mode to obtain the video monitoring data of the vehicle. Compared with the mass center and real line distance method of abundant foreground change, the method is capable of eliminating the interferences, such as vehicle tracking, blocking, pedestrian and non-motor vehicle, and improving the accuracy rate of traffic illegal act judgment.

Description

technical field [0001] The present invention relates to the field of traffic violation detection, and more specifically, to a method and system for detecting traffic violations based on vehicle tracking. Background technique [0002] With the rapid growth of urban car ownership and the limitation of urban road space, traffic violations are becoming more and more frequent. Traffic violations such as compacting lines, crossing lanes, and reverse traffic not only affect the normal traffic order, but may lead to serious traffic accidents. Automatic and accurate real-time detection of urban road traffic violations can effectively regulate the driving behavior of drivers, and at the same time can greatly improve the work efficiency of traffic police and reduce the cost of police force. [0003] At present, the detection of traffic violations is generally based on the red light signal of the street light, and the ground sense coil is set up or the traffic light signal is connected...

AI Technical Summary

Problems solved by technology

Since this method involves the calculation of the center of mass, and the size of the vehicles on the road is different, a centroid threshold cannot be well determined to detect all vehicles, and if the lane has an inclination angle, the center of mass of the vehicle will be shifted, which is more likely to cause violations misdetection of behavior

[0006] It can be seen that the above two methods have problems such as foreground mutation or centroid shift during vehicle tracking, and the accuracy of traffic violation detection is low.

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