A comparison of tracking algorithm performance for objects in wide area imagery

Object tracking is currently one of the most active research areas in computer vision. In this paper we compare and analyze the performance of six recent object tracking algorithms on a raw, low resolution, unregistered, interlaced aerial video of multiple cars moving on a roadway. This dataset comprising 50 frames of video offers a wide variety of challenges related to imaging issues such as low resolution, unregistered frames, camera motion, and interlaced video, as well as object detection problems such as low contrast, background clutter, object occlusion and varying degrees of motion. We present the performance of these algorithms in terms of both overlap accuracy and the Euclidean distance of the center pixel returned by the tracking algorithm from the ground truth.