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CORR
2008
Springer

Face Detection Using Adaboosted SVM-Based Component Classifier

11 years 1 months ago
Face Detection Using Adaboosted SVM-Based Component Classifier
: Boosting is a general method for improving the accuracy of any given learning algorithm. In this paper we employ combination of Adaboost with Support Vector Machine (SVM) as component classifiers to be used in Face Detection Task. Proposed combination outperforms in generalization in comparison with SVM on imbalanced classification problem. The proposed here method is compared, in terms of classification accuracy, to other commonly used Adaboost methods, such as Decision Trees and Neural Networks, on CMU+MIT face database. Results indicate that the performance of the proposed method is overall superior to previous Adaboost approaches.
Seyyed Majid Valiollahzadeh, Abolghasem Sayadiyan,
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where CORR
Authors Seyyed Majid Valiollahzadeh, Abolghasem Sayadiyan, Mohammad Nazari
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