Facial expression recognition using ensemble of classifiers


This paper presents a novel method for facial expression classification that employs the combination of two different feature sets in an ensemble approach. A pool of base classifiers is created using two feature sets: Gabor filters and local binary patterns (LBP). Then a multi-objective genetic algorithm is used to search for the best ensemble using as objective functions the accuracy and the size of the ensemble. The experimental results on two databases have shown the efficiency of the proposed strategy by finding powerful ensembles, which improves the recognition rates between 5% and 10%.

DOI: 10.1109/ICASSP.2011.5946775

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@article{Zavaschi2011FacialER, title={Facial expression recognition using ensemble of classifiers}, author={Thiago H. H. Zavaschi and Alessandro L. Koerich and Luiz Eduardo Soares de Oliveira}, journal={2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, year={2011}, pages={1489-1492} }