Two-Stage Recognition and beyond for Compound Facial Emotion Recognition

被引:21
|
作者
Kaminska, Dorota [1 ]
Aktas, Kadir [2 ,3 ]
Rizhinashvili, Davit [2 ]
Kuklyanov, Danila [2 ,4 ]
Sham, Abdallah Hussein [4 ]
Escalera, Sergio [5 ,6 ,7 ]
Nasrollahi, Kamal [6 ]
Moeslund, Thomas B. [6 ]
Anbarjafari, Gholamreza [2 ,3 ,8 ,9 ]
机构
[1] Lodz Univ Technol, Inst Mech & Informat Syst, PL-90924 Lodz, Poland
[2] Univ Tartu, ICV Lab, EE-50090 Tartu, Estonia
[3] IVCV OU, EE-51011 Tartu, Estonia
[4] Tallinn Univ, Enact Virtual Lab, EE-19086 Tallinn, Estonia
[5] Comp Vision Ctr, Barcelona 08193, Spain
[6] Aalborg Univ, Visual Anal & Percept Lab, DK-9220 Aalborg, Denmark
[7] Univ Barcelona, Dept Math & Comp Sci, Barcelona 08011, Spain
[8] PwC Advisory, Helsinki 00180, Finland
[9] Yildiz Tech Univ, Inst Higher Educ, TR-34349 Istanbul, Turkey
关键词
compound emotion recognition; facial expression recognition; dominant and complementary emotion recognition; deep learning; EXPRESSIONS; MODEL;
D O I
10.3390/electronics10222847
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:16
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