Visible to the public Facial Expression Recognition Based on Facial Action Unit

TitleFacial Expression Recognition Based on Facial Action Unit
Publication TypeConference Paper
Year of Publication2019
AuthorsYang, Jiannan, Zhang, Fan, Chen, Bike, Khan, Samee U.
Conference Name2019 Tenth International Green and Sustainable Computing Conference (IGSC)
Keywordsemotion recognition, face recognition, facial action unit, facial expression recognition, facial expression recognition method, facial landmark, facial landmarks, facial muscle movements, facial recognition, FER benchmark datasets, Human Behavior, human expressions, human factors, image classification, mental states, Metrics, muscle, pubcrawl, resilience, Resiliency

In the past few years, there has been increasing interest in the perception of human expressions and mental states by machines, and Facial Expression Recognition (FER) has attracted increasing attention. Facial Action Unit (AU) is an early proposed method to describe facial muscle movements, which can effectively reflect the changes in people's facial expressions. In this paper, we propose a high-performance facial expression recognition method based on facial action unit, which can run on low-configuration computer and realize video and real-time camera FER. Our method is mainly divided into two parts. In the first part, 68 facial landmarks and image Histograms of Oriented Gradients (HOG) are obtained, and the feature values of action units are calculated accordingly. The second part uses three classification methods to realize the mapping from AUs to FER. We have conducted many experiments on the popular human FER benchmark datasets (CK+ and Oulu CASIA) to demonstrate the effectiveness of our method.

Citation Keyyang_facial_2019