RTracker: Recoverable Tracking via Positive-Negative Tree Structured Memory

The proposed RTracker framework dynamically associates a tracker and a detector to enable self-recovery ability for visual object tracking. It constructs a Positive-Negative Tree (PN tree) structured memory to chronologically store and maintain positive and negative target samples, and develops corresponding walking rules to reliably determine the target state for associating the tracker and detector.