Moving vehicle speed measurement method based on target tracking and feature point matching

Abstract

The invention discloses a moving vehicle speed measurement method based on target tracking and feature point matching, and belongs to the field of intelligent traffic. The method mainly comprises the steps that a current image sequence Fn is obtained; a gray level image Y(n) of the current frame is obtained; position information P_Cur of a moving vehicle of the current frame is obtained according to background modeling; track information T of the moving target of the current frame is obtained; feature points are extracted, and information of the feature points is recorded; the feature points are matched, the moving displacement of the target is calculated, and the instant running speed of the target is obtained according to a camera calibration result; scale changes of feature points to be matched and the matched feature points are calculated according to a final matching result and then are analyzed, and algorithm parameters are updated according to the analyzing result; the average value of all instant speeds of the moving target is obtained. The method can efficiently and accurately calculate out the moving displacement of the vehicle and is applicable to the systems such as security vehicle monitoring systems and red light running electronic police systems.

Description

technical field [0001] The invention belongs to the fields of image pattern recognition, video target tracking, intelligent video monitoring and intelligent transportation, and in particular relates to a method for measuring speed of a moving vehicle based on target tracking and feature point matching; [0002] Specifically, the present invention relates to a foreground extraction method based on background modeling, a moving target tracking method based on the largest connected domain, and a moving vehicle speed measurement method based on an improved matching algorithm of SIFT feature points, which are suitable for security checkpoint systems, running red lights, etc. Electronic police system and other systems. Background technique [0003] With the rapid development of my country's economy and the sharp increase in the number of social motor vehicles, vehicle-related incidents and cases have increased exponentially. In order to improve the level of social security and re...

AI Technical Summary

Problems solved by technology

[0011] The algorithm based on motion trajectory has high efficiency and good real-time performance, and is suitable for moving into embedded devices. Due to the error between the motion trajectory information output by the algorithm and the actual motion trajectory, there is an error in the final speed measurement result; SIFT feature point matching algorithm It is a commonly used feature point matching algorithm. It is widely used because of its high matching accuracy, strong robustness, adaptability to target scale, angle and displacement changes, and the ability to overcome the influence of illumination changes. High complexity, real-time performance cannot be guaranteed

Images