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.
Principal Component Analysis (PCA) is one of the well-known and widely accepted dimensionality reduction techniques in varied domains. However, PCA does not scale well computationally with increasing dimensionality and it extracts only global features, ignoring local features. The local features may be very useful for classification. More recently, partitioning based PCA approaches (FP-PCA) have been...
In this paper we present a novel approach to recognition of faces in frontal color images. It involves face extraction, creation of face models with wavelet packet decomposition for dimensionality reduction, Principal Component Analysis (PCA) of the decomposed faces, Linear Discriminant Analysis (LDA) over the PCA subspace, neural classifiers with radial basis functions for each modality and combination...
We propose a face recognition model consisting of the following stages: facial feature localization (23 essential points, corresponding to eyes, mouth, nose, and face boundary); feature representation by Gabor wavelet based filtering (GWF); dimensionality reduction using principal component analysis (PCA); neural classification using concurrent self-organizing maps (CSOM). For the ORL face database,...
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.