Traffic target tracking method based on optical flow and local invariant features

Abstract

The invention discloses a traffic target tracking method based on optical flow and local invariant features. The method comprises the steps that firstly, an initial template is constructed for an input video image through Gaussian background modeling, and a foreground target is extracted; next, a target characteristic point is detected through the SURF transformation algorithm; then, the characteristic point is detected and the target is tracked by constructing an image multi-resolution wavelet pyramid and improving an LK sparse optical flow method, an adaptive template real-time updating strategy is made, whether the template is the last frame or not is judged, and if yes, tracking is ended; if the template is not the last frame, template updating judgment is conducted; if template updating is not needed, tracking is continued; if template updating is needed, tracking is continued after the template and a tracking window are updated according to an updating method. Through the method, matching is accurate and rapid, redundant data is reduced, adaptability is high, high robustness is achieved in respect of target vehicle deformation, high speed, noise, uneven illumination, partial covering and other complicated environments, and the vehicle recognition ability is improved; the method has obvious advantages compared with a traditional method and has good application prospects in intelligent transportation target tracking systems.

Description

technical field [0001] The invention relates to the problem of traffic target tracking in image processing and video monitoring technology, in particular to a traffic target tracking method based on optical flow and local invariant features. Background technique [0002] Target detection and tracking is one of the complex and hot research topics in the field of computer vision today; with the economic development, the number of vehicles continues to increase, and traffic accidents occur frequently; the moving target detection and tracking technology in the intelligent transportation system combines image processing, computer and automatic control Technology, real-time monitoring of traffic targets, extraction of target location, morphological structure, motion parameters and other information, to provide decision-making basis for improving traffic conditions; in recent years, optical flow technology has attracted widespread attention in the fields of pattern recognition, comp...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems of the existing optical flow target tracking methods, such as heavy computational load, poor real-time performance, inapplicability to environments with changing illumination, and easy failure in tracking fast-moving objects, the present invention provides a method based on optical flow and local invariance The characteristic traffic target tracking method, which is accurate and fast in matching, reduces redundant data, and has strong adaptability. Compared with the traditional method, the vehicle identification ability has obvious advantages, and has a good application prospect in the intelligent traffic target tracking system

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