Research of Object Tracking Algorithm Based on KernelCorrelation Filtering and Kalman Filtering
In view of the problem that target tracking often generates drift in the case of occlusion,an object tracking algorithm based on kernel correlation filter and Kalman filter is proposed.The algorithm u-ses the peak sidelobe ratio of the kernel correlation filter response to judge the occlusion.When there is no occlusion,the kernel correlation filter is used as the main tracker,the object position is obtained,and the Kalman filter is modified.When there is occlusion,the Kalman filter is set as the main tracker and the ob-ject position is estimated and keep the kernel correlation filter model not updated.The experiment com-pares the tracking speed,accuracy and success rate with other similar algorithms in qualitative and quanti-tative analysis,and the results show that the algorithm can effectively improve the tracking effect under the occlusion condition,and has strong robustness.
万方数据
维普
