Robust discriminative tracking via structured prior regularization

In this paper, we address the problem of tracking an object in a video sequence given its location in the first frame and no other information. Many existing discriminative tracking algorithms usually train a classifier in an on-line manner to separate the object of interest from the background. Slight inaccuracies in the tracking may result in incorrectly labelled training set, which can degrade the tracker. Although a number of approaches …