Aiming at problem that current model updating method only relies on the target information from the previous frame or the recent frames

and the historical information is not fully utilized

a multi-template updating strategy is designed

and a new moving target tracking method is proposed based on this updated model and convolutional network. Compared with some state-of-art trackers in VOT2015 tracking benchmark dataset

the experimental results show that the method is robust and has high accuracy for occlusion phenomena and target deformation.