the problem of eye detection in face images is very important for a large number of applications ranging from face recognition to gaze tracking. in this paper we propose a new algorithm for eyes detection. first, the face region is extracted from the image by skin-color information. second, horizontal projection in image is used to approximate region of the eye be obtained . at last, the eye ce...

Eigen values evaluation is an integral but computation-intensive part for many image and signal processing applications. Modified Gram-Schmidt Orthogonalization (MGSO) is an efficient method for evaluating the Eigen values in face recognition algorithms. MGSO applies normalization of vectors in its iterative orthogonal process and its accuracy depends on the accuracy of normalization. Using sof...

Eigenface approach is one of the simplest and most efficient methods for face recognition. In eigenface approach chosing the threshold, value is a very important factor for performance of face recognition. In addition, the dimensional reduction of face space depends upon number of eigenfaces taken. In this paper, an optimized solution for face recognition is given by taking the optimized value ...

Principal Components Analysis (PCA) is an appearance based technique used widely for the dimensionality reduction and it records a great performance in face recognition. PCA based approaches typically include two phases: training and classification (Draper et al 2003). In the training phase, an Eigen space is established from the training samples using PCA and the training face images are mappe...

Conditions for the construction of polynomial eigen–operators for the Hamiltonian of collective string field theories are explored. Such eigen–operators arise for only one monomial potential v(x) = μx2 in the collective field theory. They form a w∞– algebra isomorphic to the algebra of vertex operators in 2d gravity. Polynomial potentials of orders only strictly larger or smaller than 2 have no...

Following Futurism, we show how periodic motions can be represented by a small number of eigen-shapes that capture the whole dynamic mechanism of periodic motions. Spectral decomposition of a silhouette of an object in motion serves as a basis for behavior classiÿcation by principle component analysis. The boundary contour of the walking dog, for example, is ÿrst computed eÆciently and accurate...