Infrared target tracking method based on background perception of activation region

Abstract

The invention discloses an infrared target tracking method based on the background perception of an activation region, which mainly solves the problems that the instantaneity is poor, a template is easily influenced by interference and a tracking window is short of effective self-adaption adjustment strategies in the existing tracking technique. The infrared target tracking method disclosed by the invention comprises the following realization steps: firstly, marking out a candidate target selection and background perception effective region by establishing the activation region under a particle filtering framework and extracting the apparent characteristics by utilizing a covariance operator; then, distinguishing the current scene state of the target through the background perception of the activation region and extracting the position and dimension observation sets of the target; and finally, formulating a template renewing strategy according to the scene state, avoiding leading the interference into the template and leading and combining the target position observation and apparent characteristics to sieve the candidate targets, thereby improving the tracking accuracy and realizing the self-adaption adjustment of an observation window by simultaneously utilizing the dimension observation of the target. The infrared target tracking method disclosed by the invention has stronginterference resistance and realizes the rapid self-adaption accurate tracking on an infrared target in a strong noise wave interference environment.

Description

technical field [0001] The invention belongs to the technical field of guidance and relates to infrared target tracking, in particular to an infrared target tracking method based on background perception in an active area, which can be used in military or civilian systems such as infrared imaging guidance and monitoring. Background technique [0002] Infrared target tracking has always been a hot and difficult point in video tracking research due to the characteristics of few target image details and low signal-to-noise ratio. Among them, the lack of detailed features mainly means that the infrared image lacks color and texture information, and the distinguishability between objects is low. Therefore, infrared target tracking is more susceptible to interference than visible light, especially the interference caused by heat sources with similar shapes is more serious. In addition, the low signal-to-noise ratio will cause more error information to be involved in the feature ex...

AI Technical Summary

Problems solved by technology

However, this method still has the following shortcomings: First, the fast method of the covariance operator is global, which seriously affects the real-time performance; second, the traditional template update method is based on the estimated state in the previous continuous time period to predict the current Frame template, when there is interference, this indiscriminate update method will obviously introduce the interference state into the template, which will lead to deviation, so that the tracking accuracy after passing the interference will drop significantly, or even diverge; the third is the lack of effective The adaptive tracking window method cannot completely solve the problem of target scale changes caused by radial motion or non-rigid deformation.

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