Infrared dim target tracking based on guide filter and Bayes classification

摘要

An infrared dim and small tracking is proposed based on an explicit image filter - guided filter. The guided filter utilizes the structure in the guidance image and performs as an edge-preserving smoothing operator. The superior performance depending on the guidance image is critical advantage for target tracking. First, the guided filter can help to preserve the detail of the valuable templates and make the inaccurate ones blurry so that the tracker can distinguish the target from numerous bad templates easily. Besides, the filter can recover the content of the small target being influenced according to the guidance image, helping to alleviate the drifting problem effectively. Finally, the candidate samples are utilized to train an effective Bayes classifier to generate a robust tracker, which is easy to be implemented. Experimental results demonstrate that the presented method can track the target effectively, compared with several classical methods. Experimental results show that the proposed algorithm outperforms relative trackers in the accuracy and the robustness.