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.
Boosted tracking in video / G. Boccignone, P. Campadelli, A. Ferrari, G. Lipori. - In: IEEE SIGNAL PROCESSING LETTERS. - ISSN 1070-9908. - 17:2(2010 Feb), pp. 129-132.
Boosted tracking in video
G. BoccignonePrimo
;P. CampadelliSecondo
;G. LiporiUltimo
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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