  The aspect ratio variation frequently appears in visual tracking and has a
severe influence on performance. Although many correlation filter (CF)-based
trackers have also been suggested for scale adaptive tracking, few studies have
been given to handle the aspect ratio variation for CF trackers. In this paper,
we make the first attempt to address this issue by introducing a family of 1D
boundary CFs to localize the left, right, top, and bottom boundaries in videos.
This allows us cope with the aspect ratio variation flexibly during tracking.
Specifically, we present a novel tracking model to integrate 1D Boundary and 2D
Center CFs (IBCCF) where boundary and center filters are enforced by a
near-orthogonality regularization term. To optimize our IBCCF model, we develop
an alternating direction method of multipliers. Experiments on several datasets
show that IBCCF can effectively handle aspect ratio variation, and achieves
state-of-the-art performance in terms of accuracy and robustness.
