Fast Scale-Adaptive Correlation Tracking

Since conventional correlation tracking algorithm cannot adapt to scale variations of the target well, and the scale-pyramid based correlation trackers gain higher precision but sacrifice more speed, this paper proposes a simple and efficient scale-adaptive correlation tracking method. Firstly, we converted the target scale to translation signals by taking log-polar transformation. Then, we extracted HOG features from target in Cartesian and log-polar coordinates, and built translation and scale correlation filter models. Finally, the translation and scale factor were tracked synchronously in the framework of correlation filter and fused into tracking bounding rectangle. Experiment results demonstrate that our tracker achieves much little loss in precision comparing with scale-pyramid based correlation trackers, but performs more than twice as the latter ones in speed.