Augmented Reality Tracking Registration Based on Improved KCF Tracking and ORB Feature Detection
Wang Yangping, Jiu Yong, Zhu Zhengping, Decheng Gao · 2019
Target tracking and feature detection in 3D registration of augmented reality(AR) system are vulnerable to environment, time-consuming algorithm and low accuracy. An AR tracking registration method based on improved Kernerlized Correlation Filter(KCF) KCF tracking and ORB (Oriented FAST and Rotated BRIEF) feature detection is proposed. Firstly, KCF algorithm is employed to track the registered target position. By considering the strategy of all previous frames, the problem of real-time updating of the weight vector of the target model in KCF tracking is solved, which makes the tracking of the target position real-time and effective. ORB operator with high real-time performance is used to detect the target position. Then the feature points of the detected target position are matched, and the three-dimensional registration matrix is calculated according to the matched feature points, and the three-dimensional registration is carried out. The experimental results show that the improved method achieves better real-time performance, stability and robustness.