Face Recognition

FR,Face Recognition,faces Recognition,face recognit,face recognitions

Face Recognition - FR
Publications: 11,616| Citation Count: 135,540
Stemming Variations: faces Recognition, face recognit, face recognitions
Cumulative Annual
    • Face recognition (FR) is the preferred mode of identity recognition by humans: It is natural, robust and unintrusive. However, automatic FR techniques have failed to match up to expectations: Variations in pose, illumination and expression limit the performance of 2D FR techniques. In recent years, 3D FR has shown promise to overcome these challanges. With the availability of cheaper acquisition methods, 3D face recognition can be a way out of these problems, both as a stand-alone method, or as a supplement to 2D face recognition...


    • Face recognition is an important research area with many potential applications such as biometric security. Among various techniques, eigenface method by principal component analysis (PCA) of face images has been widely used. In traditional eigenface methods, PCA was used to get the eigenvectors of the covariance matrix of a training set of face images and recognition was achieved by applying a template matching scheme with the vectors obtained by projecting new faces along a small number of eigenfaces...

    Bai-ling Zhang Iet al. Subject-Based Modular Eigenspace Scheme for Face Recognition

    • Face Recognition is an important topic in the field of pattern recognition. This technology has a variety of applications including entrance guard control, personal service system, criminal verification, and security verification of finance. Our research focuses on the development of a human face recognition system. It is a challenge to correctly identify a human in an image under various possible situations including difference of lighting conditions, change of hairstyles, variation of facial expression, and different aspects of the face...

    Hwei-jen Linet al. An Integrated System of Face Recognition

    • Face recognition is an important biometric because of its potential applications in many fields such as access control, surveillance, and human-computer interactions. In this article, an investigation of the effect of the step size for both the angle and the vector of the Radon transform on the performance of a face recognition system based on principal component analysis (PCA) and Euclidean distance is carried out. It was found that changing the vector or the angle step size affects the performance of the system...

    Jamal Ahmad Darghamet al. Radon transform for face recognition

    • Face recognition is an important area of research with many applications, including biometric security and searching face databases. This article describes an approach to recognize faces using eigenbands, which aim to capture the best features from facial characteristics...

    George D. C. Cavalcantiet al. Eigenbands fusion for frontal face recognition

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