Abstract
Facial expression is one of the profound nonverbal channels through which human emotion state is communicated, its automation involves analysis and recognition of facial features. Facial Expression Recognition (FER) is categorized as behavioral biometrics, and also applicable in the field of computer vision and human computer interaction. Variations in the nature of the images to be processed; head pose, image background, light intensity and occlusion are some of the sources of the challenges with facial expression recognition system. Achieving a robust automatic facial expression recognition system invariant to the aforementioned challenges, is the goal of this research area. This paper presents an analysis of major feature extraction and classification methods, their performances in terms of accuracy and their respective limitations.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
