Research of meanshift tracking algorithm based on feature matching estimation

Aiming at the problem that traditional Meanshift tracking algorithm cannot track target accurately. When target is occluded or background interferences appear, a new tracking algorithm based on features matching and motion detection predicting is proposed. The new algorithm extracts features of target by the SIFT algorithm to realize the location. The original iteration position is estimated by the Kalman filter, then iterative searching of moving target starts at the location to shrink the searching scope. And finally the target tracking is realized. The results of experiment indicate that the algorithm can detect the location of tracking target accurately to improve the tracking effectively when interference exists in the cluttering background. The improved algorithm has low time complexity and strong robustness.