@inproceedings{e7d947ab4bb94092a0d1fedc72e2419b,
title = "Online learning of linear predictors for real-time tracking",
abstract = "Although fast and reliable, real-time template tracking using linear predictors requires a long training time. The lack of the ability to learn new templates online prevents their use in applications that require fast learning. This especially holds for applications where the scene is not known a priori and multiple templates have to be added online. So far, linear predictors had to be either learned offline [1] or in an iterative manner by starting with a small sized template and growing it over time [2]. In this paper, we propose a fast and simple reformulation of the learning procedure that allows learning new linear predictors online.",
keywords = "linear predictors, template learning, template tracking",
author = "Stefan Holzer and Marc Pollefeys and Slobodan Ilic and Tan, {David Joseph} and Nassir Navab",
year = "2012",
doi = "10.1007/978-3-642-33718-5_34",
language = "English",
isbn = "9783642337178",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 1",
pages = "470--483",
booktitle = "Computer Vision, ECCV 2012 - 12th European Conference on Computer Vision, Proceedings",
edition = "PART 1",
note = "12th European Conference on Computer Vision, ECCV 2012 ; Conference date: 07-10-2012 Through 13-10-2012",
}