In this note it is discussed how real-time face detection and tracking in video can be achieved by relying on a Bayesian approach realized in a multi-threaded architecture. To this end we propose a probabilistic interpretation of the output provided by a cascade of AdaBoost classifiers. Results show that such integrated approach is appealing with respect either to robustness and computational efficiency.
Real-Time Probabilistic Tracking of Faces in Video / G. Boccignone, P. Campadelli, A. Ferrari, G. Lipori - In: Image Analysis and Processing – ICIAP 2009 : 15th International Conference, Vietri sul Mare, Italy, September 8-11, 2009 : Proceedings / [a cura di] P. Foggia, C. Sansone, M. Vento. - Berlin : Springer Berlin, 2009 Sep. - ISBN 9783642041457. - pp. 672-681 (( Intervento presentato al 15. convegno International Conference on Image Analysis and Processing – ICIAP 2009 tenutosi a Vietri sul Mare, Italy nel 2009.
Real-Time Probabilistic Tracking of Faces in Video
G. BoccignonePrimo
;P. CampadelliSecondo
;G. LiporiUltimo
2009
Abstract
In this note it is discussed how real-time face detection and tracking in video can be achieved by relying on a Bayesian approach realized in a multi-threaded architecture. To this end we propose a probabilistic interpretation of the output provided by a cascade of AdaBoost classifiers. Results show that such integrated approach is appealing with respect either to robustness and computational efficiency.
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