Facial Expression Recognition in the Wild with Application in Robotics
Küçük Resim Yok
Tarih
2021
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
One of the major problems with robot companions is their lack of credibility. Since emotions play a key role in human behaviour their implementation in virtual agents is a conditio sine-qua-non for realistic models. That is, correct classification of facial expressions in the wild is a necessary preprocessing step for implementing artificial empathy. The aim of this work is to implement a robust Facial Expression Recognition (FER) module into a robot. Considering the results of an empirical comparison among the most successful deep learning algorithms used for FER, this study fixes the state-ofthe-art performance of 75% on the FER2013 database with the ensemble method. With a single model, the best performance of 70.8% has been reached using the VGG16 architecture. Finally, the VGG16-based FER module has been been implemented into a robot and reached a performance of 70% when tested with wild expressive faces. © 2021 IEEE
Açıklama
6th International Conference on Computer Science and Engineering, UBMK 2021 -- 15 September 2021 through 17 September 2021 -- -- 176826
Anahtar Kelimeler
Deep Learning, Facial Expressions Classification, Virtual Humans, Behavioral Research, Deep Learning, E-Learning, Face Recognition, Reinforcement Learning, Robotics, Robots, Virtual Reality, Deep Learning, Facial Expression Recognition, Facial Expressions, Facial Expressions Classifications, Human Behaviors, Performance, Realistic Model, Robot Companion, Virtual Agent, Virtual Humans, Learning Algorithms
Kaynak
Proceedings - 6th International Conference on Computer Science and Engineering, UBMK 2021
WoS Q Değeri
Scopus Q Değeri
N/A
