Abstract
Nowadays, analysis of human body movements for emotion recognition is essential for social communication. Non-verbal communication methods like body movements, facial expression, gestures and eye movements are used in several applications. Among them emotion recognition from body movements has an advantage of recognize emotions of person from any camera view and also recognize emotions, if person is too far from camera. The body movements can strongly convey emotional states than other studies. In this paper, emotional state recognizes from full body motion patterns using feedforward deep convolution neural network architecture with different parameter. The proposed system can be evaluated by emotion dataset (University of YORK) with 15 types of emotions and GEMEP corpus dataset with 5 emotions. The experimental result showed the better recognition accuracy of the proposed system.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.