Nnface recognition using eigenfaces pdf

The algorithm for the facial recognition using eigenfaces is basically described in figure. Face recognition using eigenfaces ucsb computer science. So, in order to reconstruct the original image from the eigenfaces, one has to build a kind of weighted sum of all eigenfaces. Recognition is performed by projecting a new image into the snb space spanned by the eigenfaces face space and then classifying the face by comparing its position in face space with the positions of known individuals. Problems arise when performing recognition in a highdimensional space. In this study an approach to recognize known faces based on eigen vectors and a hybrid metaheuristic feature selection algorithm is proposed. Recognition using class specific linear projection 7 wwsw opt w t t m arg max ww w 12k 2 where w i im12,,k is the set of ndimensional eigenvectors of s t corresponding to the m largest eigenvalues. Face recognition using eigenfaces article pdf available in international journal of computer applications 1185. An eigenface is the name given to a set of eigenvectors when used in the computer vision problem of human face recognition.

For and attribution information for the modules contained in this. An approach to the detection and identification of human faces is presented, and a working, nearrealtime face recognition system which tracks a subjects head and then recognizes the person by comparing characteristics of the face to those of known individuals is described. Face recognition using eigenface approach sjee serbian. Pdf face recognition using eigenfaces researchgate. Face recognition using eigenfaces computer vision and. These characteristic features are called eigenfaces in. Face recognition using eigenface approach 123 the next step is to calculate the covariance matrix c, and find its eigenvectors ei and eigenvalues. Pentland, eigenfaces for recognition,journal of cognitive neuroscience,vol.