A new tracking method for small infrared targets

We report on a new approach to tracking small infrared targets. The method improves on existing target trackers by combining mean-shift tracker with Kalman filtering and by updating the tracking parameters through the measurement of the complexity of the target region. We have further developed a nonlinear algorithm to improve the robustness of the traditional mean-shift tracker for small infrared targets. Experimental results demonstrate a superior performance of our method compared to existing target trackers, particularly in the environment of strong measurement noise and large variation of illumination.