Facial Expression Recognition Using Interpolation Features

In this work, a methodology for classifying emotions (such as happiness, anger and surprise) based on face images is proposed. This methodology consist of three stages: in the pre-processing stage, edge detectors and threshold algorithms are used in order to find edge information about ROIs; in the second stage (feature extraction) numeric information of pre-processing images is extracted via interpolation methods; finally, in the classification stage supervised learners such as Neural Networks, Support Vector Machines and Naïve Bayes are tested. According to the results, our approach has acceptable accuracy in order to recognize emotions.