1. A facial recognition system comprising: a station including at least one video camera for capturing a series of video frames of an individual face; and a face image processing server for generating a series of two-dimensional models of the individual face at various angles, each model based upon one of the series of video frames, combining the series of two-dimensional models of the individual face with a projecting matrix to create a three-dimensional model of the individual face, wherein the three-dimensional model is a matrix F 3D =[x 00. .. x n , y 00. .. y n , z 00. .. z n ], where x n is an x coordinate value of an nth reference point, where n is a number of facial reference points in each video frame and an integer greater than one y n is a y coordinate value of the nth reference point, and z n is a z coordinate value of the nth reference point and wherein the three-dimensional model is generated by multiplying the inverse of a projecting matrix M defined as M=[1 0 0, 0 1 0]*R Rotation where R Rotation =[cos α cos β cos α sin β sin γ−sin α cos γ cos α sin β cos γ+sin α sin γ, sin α cos β sin α sin β sin γ+cos α cos γ sin α sin β cos γ−cos α sin γ, −sin β cos β sin γ cos β cos γ ] where α is yaw, β is pitch, and γ is roll, times a matrix of two-dimensional coordinates of n facial reference points F 2D in the form [x 00 1. .. x n 1. .. x 00 t. .. x n t , y 00 1. .. y n 1. .. y 00 t. .. y n t ] and where M −1 is [R 11 1 R 12 1 , R 13 1. .. R 11 t R 12 t R 13 t , R 21 1 R 22 1 R 23 1. .. R 21 t R 22 t R 23 t ] where t is a number of series of video frames and where R ij t is an entry of the rotation matrix R Rotation of the t-th frame of series of video frames; rotating the three-dimensional model to a reference frame that corresponds to a frontal view of the individual face, generating a two-dimensional mean reference map by projecting from the rotated three-dimensional model, the mean reference map made up of the series of n facial reference points, accessing a facial database to compare the mean reference map to a series of previously-stored reference maps, each of the previously-stored reference maps including a set of previously-stored reference points, and identifying as a match an individual whose previously-stored reference map most closely matches the mean reference map.