基于相关滤波器的抗遮挡目标跟踪算法

he traditional kernel correlation filtering target tracking algorithms can not accuratelytrack in some scenes,such as scale changes and occlusions. This article proposes improvements, combinate with the adaptive kernel correlation filter algorithm, the scale transformation and the parallel-shift filter all adopt the adopt feature dimensionality reduction to increase the speed. Integrate the judgment occlusion update mechanism,if there is occlusion, stop updating the model and predict the new target position, usethe predicted information to correct the target postion. The experimental analysis of the OTB50 test video set tracking results show that the algorithm in this paper is superior to traditional algorithms in terms of anti-occlusion and speed.