Real time unmanned aerial vehicle tracking of fast moving small target on ground

In order to solve problems of occlusion and fast motion of small targets in UAV (Unmanned Aerial Vehicle) target tracking , an adaptive algorithm which fuses the improved color histogram tracking response and the correlation filter tracking response based on multi-channel HOG features is proposed to realize small target tracking with high accuracy. The state judgment index is used to determine whether the target is in a fast motion or an occlusion state. In the fast motion state, the search area is enlarged, and the color optimal model which suppresses the suspected area is used for rough detection. Then, re-detection in the location of multiple peaks in the rough detection response is carried out using the correlation filter to accurately locate the target. In an occlusion state, the model stops updating, the search area is expanded, and the current color model is used for rough detection. Then, re-detection in the place of multiple peaks in the rough detection response is carried out using the correlation filter to accurately locate the target. Experimental results show that the proposed method can track small targets accurately. The frame rate of the proposed method is 40.23 frames/second, indicating usable real-time performance.