Target tracking using interest point detection and correlation filtering

A reliable method for real-time target tracking is presented. The method is based on an interest point detector and a bank of locally adaptive correlation filters. The point detector is used to identify local regions in the observed scene around potential location of the target. The bank of correlation filters is employed to reliably detect the target and accurately estimate its position within the scene, by processing the local regions identified by the detector. Using information of past state estimates of the target the proposed algorithm predicts the state of the target in the next frame in order to perform a fast and accurate target tracking by focussing signal processing only on small regions of the scene in each frame. In order to achieve a real-time operation performance the proposed algorithm is implemented in a graphics processing unit. Experimental results obtained with the proposed method are presented, discussed, and compared with those obtained with a similar state-of-the-art target tracking algorithm.