Abstract
In this paper, we proposed a new method of monitoring patients on bed by utilizing the facial expression analyses and recognition. In this proposed method, the optical flows of the corresponding image sequence, which appeard the facial actions, were computed. Based on the optical flow projection histogram on and coordinate axes in the mouth region and the eye region, the facial action features were extracted. By utilizing the facial action feature rate of occurrence on the happiness, easiness, uneasiness, disgust, suffering and surprise, the associate memory model of facial expressions is composed to recognize the facial expressions. The classification performance of our associate memory model is demonstrated by using a training set and a testing set from the facial expression database made for our research project.
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.
