Abstract
A new facial feature extraction technique for expression recognition is proposed. We employ the spatial frequency domain information to obtain robust performance to the random noise on a image or the lighting conditions. It exhibited high ability sufficiently even if combined with a low-performance region tracking method. As an application of this technique, we have constructed a dynamic facial expression recognition system. We use hidden Markov models to utilize temporal changes in the facial expressions. The spatial frequency information and the temporal information make better rates of facial expression recognition. In the experiment, we established a correct response rate of approximately 84.1% of recognition with six categories.
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.
