MCNet : meta-clustering learning network for micro-expression recognition
Wang, Ziqi (China University of Petroleum)
Fu, Wenwen (China University of Petroleum)
Zhang, Yue (China University of Petroleum)
Li, Jiarui (China University of Petroleum)
Gong, Wenjuan (China University of Petroleum)
Gonzàlez, Jordi (Universitat Autònoma de Barcelona)

Data:	2024
Resum:	Facial micro-expressions are categorized into various types based on different criteria, and typically each major category is further divided into multiple subcategories of expressions. For traditional micro-expression recognition problems, multiple subcategories of the same emotions are indiscriminately learned and verified, leading to potential misclassification, especially with negative emotions. To address the issue of intra-class variation in micro-expressions, we propose a meta-clustering learning network for micro-expression recognition called MCNet. This approach integrates the ideas of meta-learning and clustering, hierarchically clustering subcategories within a micro-expression class to generate multiple class centers for metric-based classification. The proposed method diverges from the common strategy of metric-based meta-learning algorithms, which typically use the mean feature of all samples within the same class as the class center. Furthermore, we incorporate transfer learning into the meta-learning process to jointly alleviate overfitting caused by the scarcity of micro-expression data. We conduct extensive comparative experiments based on the leave-one-subject-out protocol on three widely used micro-expression datasets. The experimental results demonstrate the competitive performance and strong generalization ability of the proposed MCNet approach.
Ajuts:	Agencia Estatal de Investigación PID2020-120311RB-I00
Drets:	Aquest material està protegit per drets d'autor i/o drets afins. Podeu utilitzar aquest material en funció del que permet la legislació de drets d'autor i drets afins d'aplicació al vostre cas. Per a d'altres usos heu d'obtenir permís del(s) titular(s) de drets.
Llengua:	Anglès
Document:	Article ; recerca ; Versió acceptada per publicar
Matèria:	Few-shot classification ; Hierarchical clustering ; Meta-learning network ; Micro-expression recognition
Publicat a:	Journal of electronic imaging, Vol. 33, issue 2 (March 2024) , art. 23014, ISSN 1560-229X

DOI: 10.1117/1.JEI.33.2.023014

Postprint 37 p, 9.0 MB

El registre apareix a les col·leccions:
Articles > Articles de recerca
Articles > Articles publicats