Exploration of Gesture and Facial Expression-Based Emotion Recognition Models

Human–computer interaction will feel more natural once computers are able to identify and respond to nonverbal cues from humans, such as emotions. Despite the fact that a number of methods, including those based on physiological indicators, neuroimaging techniques, speech, gesture, posture, body movement, and face detection have been developed to identify human emotions. Although a lot of work has been done on reading facial expressions, speech, etc., recognizing effects from body gestures has not received as much attention. In an effort to further research in the field, we present a new exploration, comparative analysis, and challenges in modal emotion recognition by using a combination of gesture and face expression. This paper describes methods, model datasets, model information and modalities, as well as recent developments in the difficult task of automatic emotion recognition. It also explores the field of human body emotion recognition through gesture and face detection. Due to possible uses in video games, medical diagnosis, education, patient care, vehicle safety, fraud detection, and emotion detection, the field of modal emotion recognition research is broad. This paper intends to give researchers enlightenment who are interested in learning about both customary and innovatory multimodal emotion recognition methods, as well as to in a nutshell the recent wave of work on modal emotion recognition.