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.
For most physical stores, procuring customer behavior data and client management is di cult yet crucial. For stores, especially luxury stores, who value returning customers the most, identifying customer's identity and past purchase history would significantly improve the sales by personalizing the recommendation. Many chain stores utilize membership card to collect purchase information and change...
The proliferate unstructured data generated in online social networks leads to significant research advances in the recognition of user profiles (e.g., age, gender, ethnicity, etc.), but meanwhile brings new challenges. These attributes are referred to as soft biometrics and provide a semantic description of users. Identifying users' soft biometric traits in online social networks is crucial for a...
The Partial Least Squares (PLS) algorithm has been widely applied in face recognition in recent years. However, all the improved algorithms of PLS did not utilize non-negativity and sparsity synchronously to improve the recognition accuracy and robustness. In order to solve these problems, this paper proposes a novel algorithm named Two-Dimension Non-negative Sparse Partial Least Squares (2DNSPLS),...
For benefiting from incorporating the class information, partial least squares (PLS) and its two dimension version (2DPLS) have been widely employed in face recognition when extracting principal components. However, currently popular statistic methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), only learn holistic, not parts-based, representations which ignore...
In this paper, we propose a new collaborative reconstruction-based manifold-manifold distance (CRMMD) method for face recognition with image sets, where each gallery and probe sample is a set of face images captured from varying poses, illuminations and expressions. Given each face image set, we first model it as a nonlinear manifold and then the recognition task is converted as a manifold-manifold...
We present a method for computing "choking” loops—a set of surface loops that describe the narrowing of the volumes inside/outside of the surface and extend the notion of surface homology and homotopy loops. The intuition behind their definition is that a choking loop represents the region where an offset of the original surface would get pinched. Our generalized loops naturally...
In this paper, we try to address the low level image features detection and representation problem under various illuminations and in various backgrounds. We use multiple thresholds iteratively get a proper threshold value. The results of detection may have disconnected lines, or edges, or boundaries. We use morphological reconstruction and edge linking algorithm to rebuild the edge and connect the...
In this work, we propose a novel saliency-based objective quality assessment metric, for assessing the perceptual quality of decoded video sequences affected by packet loses. The proposed method weights the error at each pixel by the visual saliency of the pixel. Different weighting methods are explored and compared. Our test results show that the predicted scores by the proposed metrics correlate...
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.