Sciweavers

Share
CVPR
2012
IEEE

Real time robust L1 tracker using accelerated proximal gradient approach

7 years 6 months ago
Real time robust L1 tracker using accelerated proximal gradient approach
Recently sparse representation has been applied to visual tracker by modeling the target appearance using a sparse approximation over a template set, which leads to the so-called L1 trackers as it needs to solve an 1 norm related minimization problem for many times. While these L1 trackers showed impressive tracking accuracies, they are very computationally demanding and the speed bottleneck is the solver to 1 norm minimizations. This paper aims at developing an L1 tracker that not only runs in real time but also enjoys better robustness than other L1 trackers. In our proposed L1 tracker, a new 1 norm related minimization model is proposed to improve the tracking accuracy by adding an 2 norm regularization on the coefficients associated with the trivial templates. Moreover, based on the accelerated proximal gradient approach, a very fast numerical solver is developed to solve the resulting 1 norm related minimization problem with guaranteed quadratic convergence. The great running ti...
Chenglong Bao, Yi Wu, Haibin Ling, Hui Ji
Added 28 Sep 2012
Updated 28 Sep 2012
Type Journal
Year 2012
Where CVPR
Authors Chenglong Bao, Yi Wu, Haibin Ling, Hui Ji
Comments (0)
books