基于kalman预测和自适应模板的目标相关跟踪研究

文中提出了一种基于kalman预测和自适应模板的目标相关跟踪算法。通过kalman预测下一帧图像中目标的状态，缩小整个图像上目标检测的搜索范围，满足目标跟踪的实时性。采取自适应模板更新策略．根据目标的变化情况自动调节参考模板，提高目标跟踪的稳定性。仿真实验结果表明，算法能够随着目标的形状、大小、位置的变化快速调整参考模板，进行稳定和实时的跟踪，当目标被物体遮挡时仍能有效地跟踪目标。

Correlation-based target tracking algorithm based on kalman prediction and adaptive template

A correlation-based tracking algorithm based on kalman prediction and adaptive reference template is discussed. The target state in the next frame can be predicted using kalman prediction which can reduce the search area of the target detection, and meet the target tracking in real time. Adaptive template update strategy which can adjust the reference template based on the changes of the tracking target is used to improve the stability of target tracking. The simulation results indicate that the algorithm can quickly adjust the reference template according to the changes of the shape size and position and the target is tracked stably and real-time. The target also can be tracked efficaciously, when it is occluded.