Focusing on the two problems existed in Staple tracker, an improved target tracking algorithm based on Staple tracker is proposed. Firstly, in order to strengthen the discriminative ability of Staple tracker for gray video sequences, a histogram classifier based on locality sensitive histogram is proposed. Furthermore, as the constant merge factor in Staple tracker can not merge two classifiers optimally, an adaptive merge factor is proposed by using the relative confident coefficient. Experiment is made on OTB2013 benchmark for comparing the proposed tracker with other 9 state-of-the-art trackers. The results show that the proposed tracker has a precision of 0.814 and a success rate of 0.614, improved by 4.1% and 3.5% respectively compared with that of the Staple tracker, which indicates that the proposed tracker is more robust.