Cost-sensitive and smooth-constrained structured SVM object tracking method based on missile-borne images
When the object self-seeking munition strikes the target,the traditional object tracking method is susceptible to the influence of the mixed background,which produces model drift and thus leads to tracking failure.In recent years,with the development of structured SVM technology,the object tracking method based on structured SVM can effectively solve the problem of complex background.Under the missile-borne environment,the cost-sensitive weights are added to the structured SVM object tracking method to solve the positive-negative sample imbalance problem caused by the background mixing in the missile-borne image,and the L2 paradigm of the difference between the hyperplane normal vectors wt at the moment of t and wt-1 at the moment of t-1 is utilized as a smoothing constraint to inhibit the model drifting problem.This paper designed a solution algorithm for the model based on the principle of dual coordinate descent and implemented a multi-scale object tracking method Scale-CS_SSVM.Experimental validation on the missile-borne dataset shows that Scale-CS_SSVM achieves the optimal performance with an improvement of 5.5 and 5.0 percentage points in tracking accuracy and success rate,respectively,compared with the Scale-DLSSVM.
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