Robot vision guide is an important research area in industrial automation, and image-based target pose estimation is one of the most challenging problems. We focus on target pose estimation and present a solution based on the binocular stereo vision in this paper. To improve the robustness and speed of pose estimation, we propose a novel visual tracking algorithm based on Fourier-Mellin transform to extract the target region. We evaluate the proposed tracking algorithm on online tracking benchmark-50 (OTB-50) and the results show that it outperforms other lightweight trackers, especially when the target is rotated or scaled. The final experiment proves that the improved pose estimation approach can achieve a position accuracy of 1.84 mm and a speed of 7 FPS (frames per second). Besides, this approach is robust to the variances of illumination and can work well in the range of 250-700 lux.