A comparison study of adaptive scale estimation in correlation filter-based visual tracking methods

Recently, discriminative correlation filter-based method becomes one of the popular directions in the field of visual tracking because of its computational efficiency and excellent performance, which make it especially suitable for real-time application. Most of them are focused only on the transition estimation. However, accurate scale estimation of the target plays a very important role in long-term tracking task and is still a challenging problem. The principle of CF-based visual tracking is introduced first. The approaches of adaptive scale estimation in correlation filter-based visual tracking methods are summarized in this paper, and their performances are analyzed by experiment comparison. The works here can provide a better understanding on the scale estimation problem for correlation filter-based visual tracking. Furthermore, maybe with the same strategy, other factors in visual tracking, such as appearance variation, can be integrated into the framework to improve the performance of correlation filter-based method.