PT Journal
AU Dorota Kaminska
   Kadir Aktas
   Davit Rizhinashvili
   Danila Kuklyanov
   Abdallah Hussein Sham
   Sergio Escalera
   Kamal Nasrollahi
   Thomas B. Moeslund
   Gholamreza Anbarjafari
TI Two-stage Recognition and Beyond for Compound Facial Emotion Recognition
SO Electronics
JI ELEC
PY 2021
BP 2847
VL 10
IS 22
DE compound emotion recognition; facial expression recognition; dominant and complementary emotion recognition; deep learning
AB Facial emotion recognition is an inherently complex problem due to individual diversity in facial features and racial and cultural differences. Moreover, facial expressions typically reflect the mixture of people’s emotional statuses, which can be expressed using compound emotions. Compound facial emotion recognition makes the problem even more difficult because the discrimination between dominant and complementary emotions is usually weak. We have created a database that includes 31,250 facial images with different emotions of 115 subjects whose gender distribution is almost uniform to address compound emotion recognition. In addition, we have organized a competition based on the proposed dataset, held at FG workshop 2020. This paper analyzes the winner’s approach—a two-stage recognition method (1st stage, coarse recognition; 2nd stage, fine recognition), which enhances the classification of symmetrical emotion labels.
ER