Mouth and eyebrow segmentation for emotion recognition using interpolated polynomials

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 e...

Full description

Saved in:
Bibliographic Details
Published inJournal of intelligent & fuzzy systems Vol. 34; no. 5; pp. 3119 - 3131
Main Authors García-Ramírez, Jesús, Olvera-López, J. Arturo, Olmos-Pineda, Ivan, Martín-Ortíz, Manuel
Format Journal Article
LanguageEnglish
Published Amsterdam IOS Press BV 01.01.2018
Subjects
Classification
Decision trees
Emotion recognition
Face recognition
Feature extraction
Mouth
Neural networks
Polynomials
Segmentation
Online AccessGet full text

Cover

More Information
Summary: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.
ISSN:1064-1246
1875-8967
DOI:10.3233/JIFS-169496