A bi-subspace model for robust visual tracking
Jialue Fan, Ming Yang, Ying Nian Wu · 2008
The changes of the target’s visual appearance often lead to tracking failure in practice. Hence, trackers need to be adaptive to non-stationary appearances to achieve robust visual tracking. However, the risk of adaptation drift is common in most existing adaptation schemes. This paper describes a bi-subspace model that stipulates the interactions of two different visual cues. The visual appearance of the target is represented by two interactive subspaces, each of which corresponds to a particular cue. The adaption of the subspaces is through the interaction of the two cues, which leads to robust tracking performance. Extensive experiments show that the proposed approach can largely alleviate adaptation drift and obtain better tracking results.