To apply augmented reality technology in mobile smart devices, a novel target tracker for the embedded system of a smart mobile device was proposed. In the stage of feature description, the binary feature was segmented rapidly and discriminative binary descriptors were established by fast brightness segment. In the stage of feature matching, a sparse searching template was proposed to improve the execution efficiency of the tracking algorithm. Initial target information was stored in a static library established by the tracker and the change of target appearance was stored in a dynamic library, and the target location was tracked by comparing search information and the templates in libraries. The execution time of the tracker was compared, and the results show that sparse search templates significantly improve the execution time of the algorithm at maintaining a higher tracking accuracy, and setting the search radius to 10 is able to meet the real-time requirements of trackers. The effective capacity of the tracker was compared also. And the results indicate that the tracking error of DBRISK are 16%, 28% and 29% decrease than those of the original BRISK (Binary Robust Invariant Scalable Keypoints) under three different search radii, which means the proposed method significantly improves the accuracy of tracking method, and is applicable to the limited computing power smart mobile devices.