Improved Meanshift Tracking Algorithm Based on Optical flow
Xiaoyan Yang, Qiu Li, Caijuan He · 2023
The mean shift tracker has difficulty in tracking fast moving targets and suffers from local optimal problem. To overcome the limitation of the mean-shift tracking algorithm, a new approach is proposed by integrating the mean-shift algorithm and optical flow methods. Even with n the rough position, the mean-shift algorithm achieves precise tracking of the target. Several tracking experiments show that the proposed algorithm can effectively track fast moving target and overcome the tracking error cumulating problems.