Affiliations: Faculty of Computer Science, Benemérita Universidad Autónoma de Puebla, Puebla, México
Correspondence:
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Corresponding author. Jesús García-Ramírez, Faculty of Computer Science, Benemérita
Universidad Autónoma de Puebla, Puebla, México. E-mail: gr_jesus@outlook.com.
Abstract: Facial Expression Recognition (FER) is a research area that has been interesting for computer science community in recent years. In this paper, we propose a methodology for the three stages of a FER system. In the pre-processing stage a method based on edge detectors and thresholding operators for eyebrow and mouth segmentation is proposed; the next stage is feature extraction, we propose using polynomials as features for describing eyebrows and mouth regions. Finally, in classification stage different supervised learners such as: Neural Networks, K-Nearest Neighbors and C4.5 decision trees are tested in order to obtain a model for classifying three out of six basic emotions (anger, happiness and surprise). According to our results, the proposed approach has acceptable accuracy for predicting new examples.
Keywords: Expression recognition, face images pre-processing, supervised
classification, interpolation features
