A comparative study involving classifiers and dimensionality reduction techniques applied to facial recognition

• Matheus Araújo Universidade Estadual do Ceará
• Leonardo Costa Universidade Estadual do Ceará
• Antony Santos Universidade Estadual do Ceará
• Caio Menezes Universidade Estadual do Ceará
• Gustavo Campos Universidade Estadual do Ceará

DOI: https://doi.org/10.5753/eniac.2019.9338

Abstract

This paper presents a comparative study between the Eigenfaces and Fisherfaces techniques combined with the KNN, SVM and MLP classifiers. The Eigenfaces and Fisherfaces techniques were used to project the images from the AT&T (The database of faces) and Extended Yale B databases into a new space in order to obtain a reduction in the dimensionality of these data. The classifiers mentioned used the data designed to perform the training task and subsequent identification of the test data classes. The results were very promising in both cases, but the MLP neural network with the Fisherfaces technique obtained the best results.

Keywords: Facial Recognition, Eigenfaces, Fisherfaces, KNN, SVM, MLP

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