Kernel-based Face Detection and Tracking with Adaptive Control by Kalman Filtering

被引：0

作者：

Boumbarov, Ognian ^{[1
]}

Sokolov, Strahil ^{[1
]}

Petrov, Plamen ^{[2
]}

Sachenko, Anatoly ^{[3
]}

Kurylyak, Yuriy ^{[3
]}

机构：

[1] Tech Univ Sofia, Fac Telecommun, Sofia, Bulgaria

[2] Tech Univ Sofia, Fac Mech Engn, Sofia, Bulgaria

[3] Ternopil Natl Econom Univ, Res Inst Intelligent Comp Syst, Ternopol, Ukraine

来源：

2009 IEEE INTERNATIONAL WORKSHOP ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS | 2009年

关键词：

Face detection; face tracking; biometrics;

D O I：

10.1109/IDAACS.2009.5342944

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页码：434 / +

页数：2

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