Real-Time Probabilistic Tracking of Faces in Video

  • Giuseppe Boccignone
  • Paola Campadelli
  • Alessandro Ferrari
  • Giuseppe Lipori
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5716)

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.

Keywords

Video Clip Face Detection Probabilistic Interpretation False Acceptance Rate Multiple Object Tracking 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Giuseppe Boccignone
    • 1
  • Paola Campadelli
    • 1
  • Alessandro Ferrari
    • 1
  • Giuseppe Lipori
    • 1
  1. 1.Dipartimento di Scienze dell’InformazioneUniversità degli Studi di MilanoMilanoItaly

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