The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, we present a novel expression recognition method. Equable Principal Component Analysis (EPCA) is used as expression features representation and Linear Regression Classification (LRC) is employed as expression classifiers. EPCA maintains the useful information of the original image while reducing the dimension of feature vector data. LRC deals with the problem of face recognition as...
Equable principal component analysis (EPCA) is a powerful technique of feature extracting. It can reduce a large set of correlated variables to a smaller number of uncorrelated components. Support vector machines (SVM) is a novel pattern classification approach. It is very efficient in solving clustering problems that are not linearly separable. This paper presents a method of expression recognition...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.