Identity-Aware Facial Expression Recognition Method Based on Synthesized Images and Deep Metric Learning

Abstract

: Facial expression recognition (FER) is a challenging task because the external environment and identity characteristics could affect the classification results directly. To settle down the above-mentioned challenges, this paper proposed an identity-aware facial expression recognition method which combined images synthesis techniques and deep metric learning, and made facial images features compared then clas-sified by creating expression groups under the same identity in FER task. There are three parts in our method. The first part is a generative adversarial network, which aims to learn expression information and synthesis the expression groups. the state-of-the-art methods, the experimental results confirmed that the proposed-method was effective and progressive in FER task.