cGAN Based Facial Expression Recognition for Human-Robot Interaction

Jia Hao Deng · Gaoyang Pang · Zhibo Pang · Huayong Yang · Geng Yang

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Emotion and Mood Recognition Face recognition and analysis Face and Expression Recognition

Abstract

As an emerging research topic for proximity service (ProSe), automatic emotion recognition enables the machines to understand the emotional changes of human beings which can not only facilitate natural, effective, seamless, and advanced human–robot interaction or human–computer interface but also promote emotional health. Facial expression recognition (FER) is a vital task for emotion recognition. However, significant gap between human and machine exists in FER task. In this paper, we present a conditional generative adversarial network-based approach to alleviate the intra-class variations by individually controlling the facial expressions and learning the generative and discriminative representations simultaneously. The proposed framework consists of a generator G and three discriminators (Di,Da, andDexp). The generator G transforms any query face image into another prototypic facial expression image with other factors preserved. Armed with action units condition, the generator G pays more attention to information relevant to facial expression. Three loss functions ($L_{I}$,La, andLexp) corresponding to the three discriminators (Di,Da, andDexp) were designed to learn generative and discriminative representations. Moreover, after rendering the generated expression back to its original facial expression, cycle consistency loss is also applied to guarantee the identity and produce more constrained visual representations. Optimized by combining both synthesis and classification loss functions, the learnt representation is explicitly disentangled from other variations such as identity, head pose, and illumination. Qualitative and quantitative experimental results demonstrate the proposed FER system is effective for expression recognition.

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References

1950Equilibrium points in n -person games 2010The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression 2017AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild 2017Reliable Crowdsourcing and Deep Locality-Preserving Learning for Expression Recognition in the Wild 2005Socially Assistive Robotics 2013DISFA: A Spontaneous Facial Action Intensity Database 2014The Faces of Engagement: Automatic Recognition of Student Engagementfrom Facial Expressions 2018Reliable Crowdsourcing and Deep Locality-Preserving Learning for Unconstrained Facial Expression Recognition

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2022Facial Emotion Expressions in Human–Robot Interaction: A Survey 2019Unsupervised emotional state classification through physiological parameters for social robotics applications 2019WGAN-Based Robust Occluded Facial Expression Recognition 2020Facial expression recognition method with multi-label distribution learning for non-verbal behavior understanding in the classroom

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