Hybrid tracking algorithm recoverable from missing track by template matching
依赖模板匹配纠错的混合跟踪算法*

Mean shift tracker (MST) and template match tracker (TMT) have the total reversed characteristics in many aspects of tracking performance. In order to track object more reliable by using the complementarity of them, this paper proposed a hybrid tracking algorithm (HTA). HTA contains two target models, which was color histogram and intensity template, and used MST as primary tracker, TMT as auxiliary tracker. When primary tracker misses tracking probably caused by background clutter or total occlusion, HTA would switch to auxiliary tracker to remedy the mistake. When target is recaptured or clutter disappearances, primary tracker would be reactivated. Experimental results show the algorithm is robust to complex scene and has low computational cost.