FER in primary school children for affective robot tutors
- Luis-Eduardo Imbernón Cuadrado
- Ángeles Manjarrés Riesco
- Félix de la Paz López
- José Manuel Ferrández Vicente (dir. congr.)
- José Ramón Álvarez-Sánchez (dir. congr.)
- Félix de la Paz López (dir. congr.)
- Javier Toledo Moreo (dir. congr.)
- Hojjat Adeli (coord.)
Editorial: Springer Suiza
ISBN: 978-3-030-19651-6
Año de publicación: 2019
Páginas: 461-471
Tipo: Capítulo de Libro
Resumen
In the last few years, robotics has attracted much interest asa tool to support education through social interaction. Since Social- Emotional Learning (SEL) influences academic success, affective robot tutors have a great potential within education. In this article we report on our research in recognition of facial emotional expressions, aimed at improving ARTIE, an integrated environment for the development of affective robot tutors. A Full Convolutional Neural Network (FCNN) model has been trained with the Fer2013 dataset, and then validated with another dataset containing facial images of primary school children, which has been compiled during computing lab sessions. Our first prototype recognizesprimary school children facial emotional expressions with 69,15%accuracy. As a future work we intend to further refine the ARTIE Emotional Component with a view to integrating the main singularities of primary school children emotional expression.