Infrared face recogniton by optimum-path forest
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This paper presents a novel, fast and accurate appearance-based method for infrared face recognition. By introducing the Optimum-Path Forest classifier, our objective is to get good recognition rates and effectively reduce the computational effort. The feature extraction procedure is carried out by PCA, and the results are compared to two other well known supervised learning classifiers; Artificial Neural Networks and Support Vector Machines. The achieved performance asserts the promise of the proposed framework. ©2009 IEEE.
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Face recognition, MLP, OPF, PCA, SVM, Thermal infrared, Appearance-based methods, Artificial Neural Network, Computational effort, Forest classifiers, Infrared face recognition, Recognition rates, Acoustic generators, Classifiers, Feature extraction, Imaging systems, Neural networks, Support vector machines
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Inglês
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2009 16th International Conference on Systems, Signals and Image Processing, IWSSIP 2009.
