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Kernel-based face detection and tracking with adaptive control by Kalman filtering

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5 Author(s)
Boumbarov, O. ; Fac. of Telecommun., Tech. Univ. of Sofia, Sofia, Bulgaria ; Sokolov, S. ; Petrov, P. ; Sachenko, A.
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This paper presents an approach to face detection and tracking in video sequences. We use a set of Haar-like features to train a cascade of classifiers. Face-tracking is performed using the mean-shift algorithm. We propose a method for adaptation both of the tracking-window and of the color-distribution model in order to increase robustness to illumination changes of the environment. Minimizing of the number of iterations is achieved by using dynamic prediction with Kalman filter.

Published in:

Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2009. IDAACS 2009. IEEE International Workshop on

Date of Conference:

21-23 Sept. 2009