Análisis de bases de datos de expresiones faciales para la identificación automática de emociones centradas en el aprendizaje

Yesenia Nohemí González Meneses; Josefina Guerrero García

Ayuda

Análisis de bases de datos de expresiones faciales para la identificación automática de emociones centradas en el aprendizaje

Yesenia Nohemí González-Meneses ^[1] ; Josefina Guerrero-García ^[1]
1. [1] Benemérita Universidad Autónoma de Puebla
  
  Benemérita Universidad Autónoma de Puebla
  
  México
Localización: Revista Colombiana de Computación, ISSN 1657-2831, ISSN-e 2539-2115, Vol. 22, Nº. 2, 2021, págs. 58-71
Idioma: español
DOI: 10.29375/25392115.4300
Títulos paralelos:
- Analysis of databases of facial expressions for the automatic identification of learning-centeredemotions
Enlaces
- Texto completo (pdf)
Resumen
- español
  Este trabajo presenta el análisis del estado del arte de bases de datos de expresiones faciales para la identificación automática de emociones centradas en el aprendizaje. La obtención de datos para los procesos de reconocimiento automático en un contexto específico es esencial para su éxito. Así, este tipo de proyectos inician haciendo una revisión de la información disponible para llevar a cabo las etapas de entrenamiento y clasificación de las emociones con las técnicas computacionales que se propongan. Se describen las actividades de búsqueda de las bases de datos de expresiones faciales que capturan emociones centradas en el aprendizaje. Estas actividades formaron parte de las etapas de la metodología del trabajo para reconocer las emociones de estudiantes mientras realizaban actividades de aprendizaje en línea. Esto permitió justificar la creación de la base de datos desde la formalización de un protocolo para su captura hasta su digitalización.
- English
  This work presents the analysis of the state of the art of facial expressions databases for the automatic identification of learning-centered emotions. Obtaining data for automatic recognition processes in a specific context is essential for their success. Thus, this project begins by reviewing the information available to carry out the training and classification stages of emotions with the proposed computational techniques. The search activities of the databases of facial expressions that capture learning-centered emotions are described. These activities were part of the stages of the work methodology to recognize students' emotions while they carried out online learning activities. This allowed justifying the creation of the database, formalizing a protocol from its capture to its digitization.
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