Research On Robust Tracking Technology For Blocking Interference In Complex Scenes

As an important part of machine vision technology,target tracking technology has attracted more and more attention and has been widely applied in military and civil fields.However,due to the complexity and variability of the tracking environment,such as illumination changes,target deformation,occlusion,similar target interference and so on,the tracker is easily lost or misplaced during the tracking process,which leads to the tracking failure,and the occlusion causes the tracking failure main reason.This paper focuses on the research and improvement of moving object tracking algorithms under complex scenes.Based on Spatial-Temporal Context(STC)algorithm and Kernel Correlation Filters(KCF)algorithm,this paper studies systematically the technology of blocking interference and designs a video target tracking difficulty evaluation system.It analyzes the background factors and their own factors in the target motion,and quantitatively describes the difficulty of tracking the target in different frames of different video sequences.Aiming at the problem of low accuracy and no occlusion detection mechanism in complex scenes,an improved spatial-temporal context algorithm based on Local Binary Pattern(LBP)and a hierarchical occlusion detection algorithm based on kernel-dependent filtering are proposed,which not only effectively improves The target localization accuracy in complex scenes is robust to occlusion of the tracking process.The main research work and achievements of this paper are as follows:1.An improved spatial-temporal context algorithm based on local binary pattern is proposed.Through the experiment of the STC algorithm,it is found that the algorithm has the reduction of tracking precision caused by deformation and occlusion.To address this problem,we propose an improved method which adopts occlusion-detection strategy and uses Local Binary Pattern(LBP)to replace the gray feature.When the occlusion is detected by the tracker,the updates of classifier's parameters are stopped.For the object of linear motion,the objective prior information was used to predict the position of the object in order to solve the problem of occlusion.After the test analysis,the improved algorithm can effectively improve the tracking precision of the target,and also show good tracking stability for the occlusion target.2.A hierarchical occlusion detection algorithm based on kernel correlation filtering is proposed.When the object is seriously or completely occluded,the tracking accuracy will decrease obviously.Through the analysis of KCF,we found that when the occlusion occurred,the classifier would introduce erroneous information,it is likely to cause a decline in positioning accuracy or even failure.Therefore,based on the KCF framework,this paper introduced the occlusion detection mechanism to stop the updating of the classifier parameters when the occlusion occurred,and using LBP feature for hierarchical occlusion detection can effectively distinguish target deformation and occlusion.As to the linear motion object,the objective prior information was used to predict the position of the object in order to solve the problem of occlusion.After the test analysis,the proposed hierarchical occlusion detection algorithm can effectively detect the occlusion and carry out the corresponding treatment,showing good tracking stability.3.Video target tracking difficulty evaluation system design.It is difficult to track the targets in different frames of different video sequences.How to describe the target tracking quantitatively is helpful to judge the advantages and disadvantages of the tracking algorithms.In this paper,we propose a target tracking difficulty design scheme based on a variety of factors,using grayscale symbiotic matrix information to quantitatively describe the background complexity,using gray histogram to quantitatively describe the similarity between the background and the target,Proportions quantitatively describe the obstruction of the target,the use of edge ratio quantitative description of the importance of the target in the background.After experimental analysis,this article designed a video target tracking difficulty rating system has a good adaptability.