An Object Tracking Method by Concatenating Structural SVM and Correlation Filter

Abstract

Structural SVM trackers and correlation filter trackers have demonstrated dominant performance in recent object tracking benchmarks. However, structural SVM trackers naturally suffer from shortage of samples and low speed, and time-consuming adaption is need to relieve the correlation filter trackers from boundary effects. Thus, we design a jointed tracker by concatenating a high-speed SSVM method-DSLT and a multi feature CF method-STAPLE to realize advantage complementation. We show that the tracking precision and robustness can be improve by a large margin comparing to either single tracker with little sacrifice of speed.