Boosted Tracking in Video
Giuseppe Boccignone, Paola Campadelli, Alessandro Ferrari and Giuseppe Lipori
IEEE Journal "Signal Processing Letters" Volume 17, Number 2, 2010.

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.

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