Facial Expression Recognition via Relation-based Conditional Generative Adversarial Network

초록

Recognizing emotions by adapting to various human identities is very difficult. In order to solve this problem, this paper proposes a relation-based conditional generative adversarial network (RcGAN), which recognizes facial expressions by using the difference (or relation) between neutral face and expressive face. The proposed method can recognize facial expression or emotion independently of human identity. Experimental results show that the proposed method provides higher accuracies of 97.93% and 82.86% for CK+ and MMI databases, respectively than conventional method.

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