Aiming at the problems existing in the Mean-Shift tracking algorithm

a dynamic target tracking algorithm based on Mean-Shift tracker and the online learning detector and Kalman filter is proposed.First use the Mean-Shift tracker to track target

after the tracker fails

online learning detector can be used to detect targets and timely update target template

so as to ensure the reliability of the tracker. The introduced Kalman filter not only improves the tracking precision

but also estimates the target area to improve the detecting speed of the detector.The effective integration of the three above can effectively solve the light changes

partial occlusion or all occlusion and others which cause problem of target tracking loss.The target overlap and the frames transmitted per second are above 0.70 and 18 fps

which show that the proposed algorithm has the advantages of high tracking precision and strong real-time performance.