Facial Expression Recognition Based on Feature Sets and Classifiers
Gao Pa · Journal of Henan University of Science & Technology · 2014
This paper presents a novel method for facial expression recognition that employs the combination of two different feature sets in an ensemble approach. A pool of base support vector machine classifiers was created using Gabor filters and local binary patterns. Then a multi-objective genetic algorithm was used to search for the best ensemble used as objective function,insuring the minimization of both the error rate and the size of the ensemble. Experimental results on JAFFE and Cohn-kanade databases show that the proposed strategy,improves the recognition rates by 5% and 10% than conventional approaches using single feature sets and single classifiers.