Ensemble based face recognition using discriminant PCA Features

Abstract

Principal Component Analysis (PCA) is one of the most widely used subspace projection technique for face recognition. In subspace methods like PCA, feature selection is fundamental to obtain better face recognition. However, the problem of finding a subset of features from a high dimensional feature set is NP-hard. Therefore, to solve the feature selection… (More)
DOI: 10.1109/CEC.2012.6256523

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