To improve the speed of Staple target tracking algorithm, dimension reduction of the extracted image features is carried out by using Principal Component Analysis(PCA)in the process of learning translation filters. In the process of learning scale filters, the number of extracted samples with different scales is reduced from 33 to 17, and scale reduction is carried out by using QR-factorization. Scale response number is increased to 33 by interpolation to ensure scale estimation accuracy. Simulation results show that detection accuracy is almost unchanged and the tracking speed is improved by about 50% in comparison with Staple algorithm.