Fast and accurate holistic face recognition using optimum-path forest

Authors:
João P. Papa;Alexandre X. Falcão;Alexandre L. M. Levada;Débora C. Corrêa;Denis H. P. Salvadeo;Nelson D. A. Mascarenhas
Affiliations:
University of Campinas, Computer Science Institute;University of Campinas, Computer Science Institute;University of São Paulo, Physics Institute of São Carlos;University of São Paulo, Physics Institute of São Carlos;Federal University of São Carlos, Computer Science Department;Federal University of São Carlos, Computer Science Department
Venue:
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Year:
2009

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Abstract

This paper presents a novel, fast and accurate holistic method for face-recognition using the Optimum-Path Forest (OPF) classifier. Our objective is to improve the face recognition accuracy against traditional methods and to reduce the computational effort in face recognition tasks. During the feature extraction stage we apply Principal Component Analysis to reduce feature vectors in several dimensionalities. Experiments using face images from three public datasets (ORL, CBCL and YALE) present good results. Comparison among two other widely used supervised classifiers, Artificial Neural Networks based on Multilayer Perceptron and Support Vector Machines, show that the proposed method drastically reduces the computational cost, achieving correct classification rates at least identical to SVM.