Online select feature target tracking
在线特征选择的目标跟踪*

In order to improve robustness of tracking system under complex surrounding such as low-contrast, similar to object interference, this paper proposed that online select optimal color feature mechanism was embedded in target tracking algorithm. The target region of current moment was seen as the target region, employed Kalman filter predict the target position in next moment, and selected a region in the predicted position as the background region. Employ this two region online learning and select the optimal color feature as tracking feature of the next moment. The Kalman filter predicted position as initial position,utilized Mean-shift search the target position.Used this searched position as measurement correct the Kalman filter.Experimental results show that this method can greatly improve the robustness of target tracking method under complex surrounding such as low-contrast, similar to object interference.