Enhanced Broad Siamese Network for Facial Emotion Recognition in Human–Robot Interaction

Robotics is one important domain of artificial intelligence applications. Proliferation of robotics makes our lives more convenient and colorful. Emotion recognition is one important task for a robot to communicate with human beings. Although different works have been proposed to complete the task of emotion recognition, conventional methods often require a lot of time and memory resources. Since a robot is often required to react timely and equipped with limited resources, we propose an enhanced Siamese network algorithm to resolve such a problem. We combine Siamese network with broad learning system while further improving mechanism of similarity metric. Experiment results show that our method can achieve a comparable performance to conventional deep learning method while reducing consumption of computing time and memory resources.