Object Tracking in UAV Videos by Multifeature Correlation Filters With Saliency Proposals

The purpose of object tracking is to locate a given target in image sequence, such as people and vehicles. In recent years, with the development of unmanned aerial vehicle (UAV) technology, object tracking in UAV videos has engaged many scholars. It has been widely used in traffic control, water quality inspection, wildlife census, and other fields. However, low resolution, scale change, occlusion, and other challenges have been restricting the development of the tracker. To solve the aforementioned problems, we put forward multifeature correlation filters with saliency proposals. First, we use histogram of oriented gradient features, gray (I) features, and color names features to heighten the representation information of the target, so that our algorithm can accurately locate small targets. Then, we introduce saliency proposals to reposition the occluded target. Finally, we use dynamic update weights instead of the fixed update weights to mitigate the adverse effects caused by template degradation. Experiments demonstrate that our tracker has achieved satisfactory tracking accuracy and AUC scores have reached 0.462, 0.417, and 0.425 on UAV123@10FPS, UAV20 L, and UAVDT datasets, respectively.