Object Tracking Based On Tracking-Learning-Detection
Rupali S. Chavan, Swapnil Patil · 2013
In this paper; we present a novel tracking framework (TLD) approach for long-term tracking of unknown objects in a video stream. The object is defined by its location and extent in a single frame. A novel tracking framework (TLD) that explicitly decomposes the long-term tracking task into tracking, learning and detection. The tracker follows the object from frame to frame. The detector localizes all appearances that have been observed so far and corrects the tracker if necessary. The learning estimates detector's errors and updates it to avoid these errors in the future. A novel learning method (P-N learning) which estimates the errors by a pair of experts: (i) P-expert estimates missed detections, and (ii) N-expert estimates false alarms. The learning process is modeled as a discrete dynamical system and the conditions under which the learning guarantees improvement are found.