Face Detection Using Adaboosted SVM-based Component Classifier
نویسندگان
چکیده
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.
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