@article{ref1,
title="Boosted Tracking in Video",
journal="IEEE signal processing letters",
year="2010",
author="Boccignone, Giuseppe and Campadelli, Paola and Ferrari, Alessandro and Lipori, Giuseppe",
volume="17",
number="2",
pages="129-132",
abstract="We discuss how a probabilistic interpretation of the output provided by a cascade of boosted classifiers can be exploited for Bayesian tracking in video streams. In particular, real-time face and body detection can be achieved by relying on such a Bayesian framework. Results show that such integrated approach is appealing with respect both to robustness and computational efficiency.<p />",
language="",
issn="1070-9908",
doi="10.1109/LSP.2009.2030862",
url="http://dx.doi.org/10.1109/LSP.2009.2030862"
}