Our objective is to develop a robust emotion recognition system based on facial expressions, with a particular
emphasis on two key regions: the eyes and the mouth. This paper presents a comprehensive analysis of emotion recognition
achieved through the examination of various facial regions. Facial expressions serve as invaluable indicators of human
emotions, with the eyes and mouth being particularly expressive areas. By focusing on these regions, we aim to accurately
capture the nuances of emotional states.
Our experimental methodology involved employing various classification techniques to assess performance
across different models. Among these, SVM exhibited exceptional performance, boasting an impressive accuracy rate of
99.2 %. This outstanding result surpassed the performance of all other methods examined in our study. Through meticu-
lous examination and experimentation, we explore the effectiveness of different facial regions in conveying emotions. Our
analysis encompasses two datasets and evaluation methodologies to ensure a comprehensive understanding of emotion
recognition capabilities.
Descripción:
Artículo científico sobre reconocimiento de emociones a partir de microexpresiones
Reconocimiento de Emociones Mediante Región de Ojos Utilizando Características Texturales, lbp y hog
Autor
Domínguez Jalili, Laura
Espejel Cabrera, Josué
Cervantes, Jair
García Lamont, Farid
Fecha de publicación
2024-10-01
Editor
Tecnura
Tipo de documento
Artículo
Palabras clave
Emotion recognition
regions
textural features
LBP
HoG
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