CASIA OpenIR  > 模式识别国家重点实验室  > 生物识别与安全技术研究
Dominant and Complementary Emotion Recognition from Still Images of Faces
Jianzhu Guo; Zhen Lei; Jun Wan
Source PublicationIEEE Access
2018
Volume6Issue:1Pages:2169-3536
AbstractEmotion recognition has a key role in affective computing. Recently, fine-grained emotion analysis, such as compound facial expression of emotions, has attracted high interest of researchers working on affective computing. A compound facial emotion includes dominant and complementary emotions (e.g. happily-disgusted, sadly-fearful), which is more detailed than the seven classical facial emotions (e.g. happy, disgust, etc.). Current studies on compound emotions are limited to use datasets with limited number of categories and unbalanced data distributions, with labels obtained automatically by machine learning-based algorithms which could lead to inaccuracies. To address these problems, we released the iCV-MEFED dataset, which includes 50 classes of compound emotions and labels assessed by psychologists. The task is challenging due to high similarities of compound facial emotions from different categories. In addition, we have organized a challenge based on the proposed iCV-MEFED dataset, held at FG workshop 2017. In this paper, we analyze the top three winner methods and perform further detailed experiments on the proposed dataset. Experiments indicate that pairs of compound emotion (e.g. surprisingly-happy vs happily-surprised) are more difficult to be recognized if compared to the seven basic emotions. However, we hope the proposed dataset can help to pave the way for further research on compound facial emotion recognition.
KeywordDominant And Complementary Emotion Recognition Compound Emotions Fine-grained Face Emotion Dataset
Indexed BySCI
WOS IDWOS:000434935200001
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21704
Collection模式识别国家重点实验室_生物识别与安全技术研究
AffiliationCenter for Biometrics and Security Research & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Jianzhu Guo,Zhen Lei,Jun Wan. Dominant and Complementary Emotion Recognition from Still Images of Faces[J]. IEEE Access,2018,6(1):2169-3536.
APA Jianzhu Guo,Zhen Lei,&Jun Wan.(2018).Dominant and Complementary Emotion Recognition from Still Images of Faces.IEEE Access,6(1),2169-3536.
MLA Jianzhu Guo,et al."Dominant and Complementary Emotion Recognition from Still Images of Faces".IEEE Access 6.1(2018):2169-3536.
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