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.
The collaborative representation-based classifier (CRC) is proposed as an alternative to the sparse representation based classifier (SRC) for image face recognition. CRC solves an l2-regularized least squares formulation, with algebraic solution, while SRC optimizes over an I1-regularized least squares problem. As an extension of CRC, the weighted collaborative representation-based classifier (WCRC)...
In this paper, a novel regularized nearest points (RNP) method is proposed for image sets based face recognition. By modeling an image set as a regularized affine hull (RAH), two regularized nearest points (RNP), one on each image set's RAH, are automatically determined by an efficient iterative solver. The between-set distance of RNP is then defined by considering both the distance between the RNPs...
Recently a collaborative representation (CR) based classification with regularized least squares (CRC-RLS) has been proposed for the classification of faces. CRC-RLS is a simple yet fast alternative to sparse representation (SR) based classification (SRC). While SR is the solution to an l1-regularized least square decomposition, CR starts from an l2-regularized least square formulation. In this paper...
In this paper we present a fully automatic system for face augmentation on mobile devices. A user can point his mobile phone to a person and the system recognizes his or her face. A tracking algorithm overlays information about the identified person on the screen, thereby achieving an augmented reality effect. The tracker is running on the mobile client, while the recognition is running on a server...
We propose a novel approach to unsupervised facial image alignment. Differently from previous approaches, that are confined to affine transformations on either the entire face or separate patches, we extract a nonrigid mapping between facial images. Based on a regularized face model, we frame unsupervised face alignment into the Lucas-Kanade image registration approach. We propose a robust optimization...
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.