Real-time emotional recognition for sociable robotics based on deep neural networks ensemble

• Autores: Nazir Kamal, Mikel Val Calvo, Jose Ramón Álvarez, Alejandro Díaz Morcillo, José Manuel Ferrández Vicente, Eduardo Fernández Jover, Tarik Boudghene Stambouli´
• Localización: Understanding the Brain Function and Emotions: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019 Almería, Spain, June 3–7, 2019 Proceedings, Part I / José Manuel Ferrández Vicente (dir. congr.), José Ramón Álvarez Sánchez (dir. congr.), Félix de la Paz López (dir. congr.), Francisco Javier Toledo Moreo (dir. congr.), Hojjat Adeli (dir. congr.), 2019, ISBN 978-3-030-19591-5, págs. 171-180
• Idioma: inglés
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• Resumen

  • Recognizing emotions in controlled conditions, based onfacial expressions, has achieved high accuracies in the past years. This is still a challenging task for robots working in real-world scenarios due to different factors such as illumination, pose variation or occlusions. One of the next barriers of science is to give sociable robots the ability to fully engage in emotional interactions with users. In this paper a real-time emotion recognition system using a YOLO-based facial detection system and an ensemble CNN for sociable robots, is proposed.Experiments have been carried out on the most challenging atabase, FER 2013, giving a performance of 72.47% on test sets, achieving current standards.