Detection Based Multipath Correlation Filter for Visual Object Tracking

This paper presents a novel detection based multipath correlation filter (DT-MPT) for moving single object tracking from Unmanned Aerial Vehicles (UAVs). Most object trackers suffer under complicated situations such as the fast motion of objects, camera motion, similar objects, and occlusions, usually found in UAV videos. This paper utilizes a correlation filter based tracking algorithm along with a motion estimation block, a novel detection block, and a new multipath block to cope with those challenges. The detection block uses the concept of the difference image to detect moving objects, while the multipath block considers multiple positions for a few looks ahead frame for accurate localization of an object position. The performance analysis on three challenging benchmark datasets UAV123@10fps, UAV20L and DTB70 show that the proposed tracker DT-MPT outperforms its base tracker as well as most of the other top-performing state of art correlation filter-based trackers while running in almost real-time.