The invention relates to an adaptive partitioned kernel correlation filter tracking method, HOG feature are extracted in unit of superpixel block, gray feature, texture feature training classifier, The tracking response graph is calculated, and the average peak correlation energy is calculated according to the response graph. When the energy value of any block is less than the threshold value, thetracking is proved to be lost. The block division method is re-selected based on the aspect ratio of the target region in the previous frame, otherwise, the final position and size of the target areobtained according to the mutual position relationship between each block. When the aspect ratio of the target changes significantly, the accurate tracking results can not be obtained. The method of the invention can self-adaptively partition to avoid the tracking result error under the condition that the aspect ratio of the target is changed, and the classifier is trained based on the HOG feature, the gray feature and the texture feature of the super pixel, and the tracking loss judgment is carried out according to the average peak correlation energy, so that the fast, accurate and effectivetarget tracking can be realized.
Adaptive block-based kernel correlation filter tracking method